The Synthetic Nervous System (SNS) is a biologically inspired neural network (NN). Due to its capability of capturing complex mechanisms underlying neural computation, an SNS model is a candidate for building compact and interpretable NN controllers for robots. Previous work on SNSs has focused on applying the model to the control of legged robots and the design of functional subnetworks (FSNs) to realize dynamical systems. However, the FSN approach has previously relied on the analytical solution of the governing equations, which is difficult for designing more complex NN controllers. Incorporating plasticity into SNSs and using learning algorithms to tune the parameters offers a promising solution for systematic design in this situation. In this paper, we theoretically analyze the computational advantages of SNSs compared with other classical artificial neural networks. We then use learning algorithms to develop compact subnetworks for implementing addition, subtraction, division, and multiplication. We also combine the learning-based methodology with a bioinspired architecture to design an interpretable SNS for the pick-and-place control of a simulated gantry system. Finally, we show that the SNS controller is successfully transferred to a real-world robotic platform without further tuning of the parameters, verifying the effectiveness of our approach.

How we interact with our environment largely depends on both the external cues presented by our surroundings and the internal state from within. Internal states are the ever-changing physiological conditions that communicate the immediate survival needs and motivate the animal to behaviorally fulfill them. Satiety level constitutes such a state, and therefore has a dynamic influence on the output behaviors of an animal. In predatory insects like the praying mantis, hunting tactics, grooming, and mating have been shown to change hierarchical organization of behaviors depending on satiety. Here, we analyze behavior sequences of freely hunting praying mantises (Tenodera sinensis) to explore potential differences in sequential patterning of behavior as a correlate of satiety. First, our data supports previous work that showed starved praying mantises were not just more often attentive to prey, but also more often attentive to further prey. This was indicated by the increased time fraction spent in attentive bouts such as prey monitoring, head turns (to track prey), translations (closing the distance to the prey), and more strike attempts. With increasing satiety, praying mantises showed reduced time in these behaviors and exhibited them primarily towards close-proximity prey. Furthermore, our data demonstrates that during states of starvation, the praying mantis exhibits a stereotyped pattern of behavior that is highly motivated by prey capture. As satiety increased, the sequenced behaviors became more variable, indicating a shift away from the necessity of prey capture to more fluid presentations of behavior assembly.

RAMBLER Robot is designed for researching insect inspired behavioral control algorithms. To evaluate these algorithms, RAMBLER Robot needs autonomous localization without typical sensors like wheel odometers or GPS. The primary objective of this work is to independently, accurately, and robustly recover the path of a moving robotic system with low-cost sensors available off-the-shelf. The computationally efficient power center method of triangulation is compared to a particle filter approach. With three passive indistinguishable landmarks at corners of a small arena, RAMBLER Robot successfully localizes with an RMS error of 2.27cm compared to an overhead camera ground truth.

Gecko-inspired structured adhesives will be valuable for novel climbing and space robots. Robots also provide useful evaluation platforms for these adhesives. Climbing robots need to be lightweight, and thus many designs use multiple feet on a single rotating wheel-leg. Generally, such designs have not been able to walk robustly on steeper than vertical substrates. In this work, we use an improved version of our previous Mushroom-Shaped Adhesive MicroStructured (MSAMS) tape to support a power-autonomous robot reliably walking inverted on glass ceilings. The resulting speeds are greater than one body/length per second, faster than other adhesion-based climbing prototypes. The printed robot design is also a contribution toward future robotic designs and will have future applications in testing new adhesives for robotic feet.

Using a new hardware implementation of our designs for tunably compliant spine-like tensegrity robots, we show that the NASA Tensegrity Robotics Toolkit can effectively generate and predict desirable locomotion strategies for these many degree of freedom systems. Tensegrity, which provides structural integrity through a tension network, shows promise as a design strategy for more compliant robots capable of interaction with rugged environments, such as a tensegrity interplanetary probe prototype surviving multi-story drops. Due to the complexity of tensegrity structures, modeling through physics simulation and machine learning improves our ability to design and evaluate new structures and their controllers in a dynamic environment. The kinematics of our simulator, the open source NASA Tensegrity Robotics Toolkit, have been previously validated within 1.3% error on position through motion capture of the six strut robot ReCTeR. This paper provides additional validation of the dynamics through the direct comparison of the simulator to forces experienced by the latest version of the Tetraspine robot. These results give us confidence in our strategy of using tensegrity to impart future robotic systems with properties similar to biological systems such as increased flexibility, power, and mobility in extreme terrains.

The Tri-Wheel is a novel wheel-leg locomotion concept inspired by work with first responders. Through its two modes of operation-Driving Mode and Tumbling Mode- this mechanism is able to both drive quickly on smooth surfaces at roughly 1.7 times desired speed and climb objects as tall as 67% of the diameter of the mechanism. The unique gearing configuration that facilitates these dual capabilities is described, and testing quantifies that this nonprecision gearing system is roughly 81% efficient in a worst-case scenario of loading. This work introduces the Tri-Wheel concept and provides preliminary testing to validate its predicted operating characteristics.

We present MantisBot, a 28 degree of freedom robot controlled by a high-fidelity neural simulation. It is modeled after the mantis, with many degrees of freedom, because we intend to study directed behaviors and leg multi-functionality, such as prey tracking and striking. As a first step, we present a distributed reflexive posture controller. MantisBot maintains posture through a series of reflexes observed in insects, specifically: strain measurements from a leg produce proportional torque commands (reflex A); large or rapidly decreasing leg strains produce a rapid, single “restep” (reflex B); a leg can only restep if its neighboring legs are all under strain (reflex C); and a leg will search for the ground if it does not reach it as expected (reflex D). All of these reflexes contribute to a hardware platform's posture, and are implemented in a highly distributed fashion. The two most distal joints in each leg each has its own central pattern generator (CPG, 12 total), upon which all of these behaviors depend. To achieve the desired dynamics, we implement a control network of conductance-based neurons with persistent sodium channels arranged in a network like the animal may possess in its thoracic ganglia. The result is a robot capable of actively maintaining posture without a centralized planner or body model. In addition, the network implementation is fast, calculating network dynamics 150 times faster than real time.

The Biologically Inspired Robotics group at Case Western Reserve University has developed several innovative designs for a new kind of robot that uses peristalsis, the method of locomotion used by earthworms. Unlike previous wormlike robots, our concept uses a continuously deformable outer mesh that interpolates the body position between discrete actuators. Here, we summarize our progress with this soft hyper-redundant robot.

Cockroach shelter-seeking strategy may look like an undirected random search, but we show that they are attracted to darkened shelters, arriving at a shelter in about half the time it would otherwise take. We were able to identify four statistically significant trends from the behavior of 134 cockroaches in one-minute naïve walking trials with four different arena configurations. By combining these trends into a model, we arrive at an algorithm that significantly directs a simulated agent to a location. This algorithm was then adapted and tested on a small mobile robot equipped with an onboard camera and antenna-like contact sensors.

The ability to autonomously track a fluid-borne odor has numerous engineering applications and natural occurrences. Engineering systems can use odor-guided navigation in tasks ranging from search and rescue to locating dangerous chemicals. Animals use odors to locate food and mates. For animals in strong unsteady turbulent flow environments where the wind is intermittent and occasionally vanishes, there is an ecological benefit to maintaining wind-driven tracking behavior. This has been shown in experiments performed using moths and cockroaches, where animals that began tracking odor in wind maintained their wind driven tracking behavior and eventually located the source after the wind was shut off during their tracking behavior. Here, we use RoboMoth, a previously developed 3D odor-tracking robot, to replicate these experiments. Our results can aid biologists in understanding how animals track odors in dynamic environments. In engineering, this study provides a first step in a hardware system towards linking odor tracking in strong wind environments to tracking in zero/low flow environments by studying the transition between the two regimes. This can help further engineers' efforts to design odor-tracking systems capable of negotiating diverse and dynamic environments. Our study of the transition from using the wind as a primary directional cue to relying on odor and an established tracking direction appears to be novel in an engineering context and unique to our work.

A prototype active Ankle Foot Orthosis has been developed to control and assist plantar flexion and dorsiflexion using an innovative series elastic actuator integrated into a standard passive AFO. A motor controls the moment arm (Insertion Point Eccentricity Control or IPEC) of a pretensioned spring, and though the magnitude of the spring force remains relatively constant, the changing moment arm produces torque about the ankle. The IPEC AFO is able to provide 3.51 Nm about the ankle in dorsiflexion and 3.88 Nm in plantar flexion with a spring modulus of 3110 N/m and an initial tension of 77 N. The torque was sufficient to prevent toe-drag during swing phase. This technology may benefit users with drop-foot or other ankle disorders, including those who have suffered stroke or spinal cord injury.

While soft-bodied animals have an extraordinarily diverse set of robust behaviors, soft-bodied robots have not yet achieved this flexiblity. In this paper, we explore controlling a truly continuously deformable structure with a CPG-like network. Our recently completed soft wormlike robot with a continuously deformable outer mesh, along with a continuum analysis of peristalsis, has suggested the neural control investigated here. We use a Wilson-Cowan neuronal model in a continuum arrangement that mirrors the arrangement of muscles in an earthworm. We show that such a system is well suited to incorporate sensory input and can create both rhythmic and nonrhythmic activity. The system can be controlled using straightforward descending signals whose effects are largely decoupled and can modulate the properties from CPG-like behaviors to static waves. This approach will be useful for designing robotic systems that express multiple adaptive behavioral modes.

A robot is being developed for urban search and rescue missions. USAR Whegs™ implements several new features into Whegs™ robot design. It is the first quadruped Whegs™ robot of this scale. It uses differential steering and the user can rapidly change its running gear to and from tracks and wheel-legs. This is also the first implementation of carbon fiber wheel-legs on a Whegs™ vehicle. The carbon-fiber reduces the mass moment of inertia eight times compared to previous aluminum designs. The running gear can be changed in 30 seconds and the resulting connections are secure. GeoSystems Zippermast allows a camera to be deployed as high as eight feet above the robot. The robot is 47.6 cm long, can travel 1.9 meters per second on its tracks, and can climb 15 cm obstacles using its wheel-legs. A two-speed transmission is being developed to permit it to run more slowly on wheel-legs for better control on irregular terrain.

Biological inspiration has long been pursued as a key to more efficient, agile and elegant control in robotics. It has been a successful strategy in the design and control of robots with both biologically abstracted and biomimetic designs. Behavioral studies have resulted in a good understanding of the mechanics of certain animals. However, without a better understanding of their nervous systems, the biologically-inspired observation-based approach was limited. The findings of Hess and Büschges, and Ekeberg et al. describing the neural mechanisms of stick insect intra-leg joint coordination have made it possible to control models of insect legs with a network of neural pathways they found in the animal's thoracic ganglia. Our work with this model, further informed by cockroach neurobiological studies performed in the Ritzmann lab, has led to LegConNet (Leg Controller Network). In this paper we show that LegConNet controls the forward stepping motion of a robotic leg. With hypothesized additional pathways, some later confirmed by neurobiology, it can smoothly transition the leg from forward stepping to turning movements. We hypothesize that commands descending from a higher center in the nervous system inhibit or excite appropriate local neural pathways and change thresholds, which, in turn, create a cascade of reflexes resulting in behavioral transitions.

We have developed several innovative designs for a new kind of robot that uses peristalsis for locomotion, the same method that earthworms use, and report on the first completed prototype (Fig. 1). This form of locomotion is particularly effective in constrained spaces, and although the motion has been understood for some time, it has rarely been effectively or accurately implemented in a robotic platform. We address some reasons for this, including some common misconceptions within the field. We present a technique using a braided mesh exterior to produce fluid waves of motion along the body of a worm-like robot. We also present a new analytical model of this motion and compare predicted robot velocity to a 2-D simulation. Unlike previous mathematical models of peristaltic motion, our model suggests that friction is not a limiting factor in robot speed, but only in acceleration. The concept is highly scalable, and we present methods of construction at two different scales.

This paper is an update on the investigation of Distributed Inward Gripping (DIG) as a rapid and robust attachment mechanism for vertical and inverted climbing. DIG is implemented on an 18-DOF hexapod, DIGbot, with onboard power and control system. Passive compliance in the foot, which is inspired by the flexible tarsus of the cockroach, increases the robustness of the adhesion strategy and enables DIGbot to execute large steps and stationary turns while walking vertically on mesh screen. Results of vertical climbing are shown.

Insects have long been a source of inspiration for the design and implementation of legged robots. Their extraordinary mobility, agility, and adaptability are features sought after when developing competent, useful mobile walkers. Externally witnessed behaviors have been successfully implemented in walking robots for decades with great success. More recent years of biological study have solved some of the mysteries surrounding the actual neurobiological methods for mobilizing these legged wonders. This paper describes the first implementation of these neurobiological mechanisms in a physical hexapod robot that is capable of generating adaptive stepping actions with the same underlying control method as an insect.

We investigate the existence of computationally inexpensive first and second order statistics that uniquely describe grass for application in an autonomous lawnmower. We then segment images based on these statistics to determine locations of driveable terrain in an image. Tight statistical clustering of illuminated grass versus artificial texture suggests that this method is sufficient for identifying driveable terrain for an autonomous lawnmower.

When a camera is affixed on a dynamic mobile robot, image stabilization is the first step towards more complex analysis on the video feed. This paper presents a novel electronic image stabilization (EIS) algorithm for highly dynamic mobile robotic platforms. The algorithm combines optical flow motion parameter estimation with angular rate data provided by a strapdown inertial measurement unit (IMU). A discrete Kalman filter in feedforward configuration is used for optimal fusion of the two data sources. Performance evaluations are conducted using a simulated video truth model (capturing the effects of image translation, rotation, blurring, and moving objects), and live test data. Live data was collected from a camera and IMU affixed to the DAGSI Whegs mobile robotic platform as it navigated through a hallway. Template matching, feature detection, optical flow, and inertial measurement techniques are compared and analyzed to determine the most suitable algorithm for this specific type of image stabilization. Pyramidal Lucas-Kanade optical flow using Shi-Tomasi good features in combination with inertial measurement is the EIS algorithm found to be superior. In the presence of moving objects, fusion of inertial measurement reduces optical flow root-mean-squared (RMS) error in motion parameter estimates by 40%.

Design modifications have improved the durability and performance of a previously developed hybrid vehicle capable of both aerial and terrestrial locomotion. Whereas the original vehicle could fly, land, and crawl in sequence, it suffered from limited durability, as evidenced by catastrophic failure after a small number of landings - two to four depending on the substrate. The two most common failure modes were breakage of the terrestrial locomotion drive servos and separation of components from the fuselage. Evaluation of the original vehicle also identified the need for an autopilot. This further complicated the durability problem by greatly increasing the vehicle's mass, causing larger impulses in high speed landings. The new fuselage design includes a well-defined nacelle to which the propeller motor is securely mounted. All metal DC motors replace R/C servos in the terrestrial drive system, and a slip clutch limits the torque experienced by the motor during landing. The slip clutch comprises an annulus that drives a concentric shaft through three quad profile orings. The new 350 gram vehicle has survived eight landings on different substrates with no sign of damage.

Successful long-term settlements on the Moon will need a supply of resources such as oxygen and water, yet the process of regularly transporting these resources from Earth would be prohibitively costly and dangerous. One alternative would be an approach using heterogeneous, autonomous robotic teams, which could collect and extract these resources from the surrounding environment (in-situ resource utilization). The Whegs¿ robotic platform, with its demonstrated capability to negotiate obstacles and traverse irregular terrain, is a good candidate for a lunar rover concept. In this research, Lunar Whegs¿ is constructed as a proof-of-concept rover that would be able to navigate the surface of the moon, collect a quantity of regolith, and transport it back to a central processing station. The robot incorporates an actuated scoop, specialized feet for locomotion on loose substrates, light detection and ranging (LIDAR) obstacle sensing and avoidance, and sealing and durability features for operation in an abrasive environment.

For decades, insects have been a valuable source of inspiration for mechanical and control designs of legged robots. Anatomical and behavioral studies of insects such as cockroaches, stick insects and locusts have inspired the development of many robots. However, their control systems had to be engineered based upon behavioral studies and control hypotheses rather than neurobiology. Recent insect neurobiological discoveries now make it possible to control the legs of robots with a network found to control the legs of stick insects. In previous work this network we have dubbed SCASM (Sensory-Coupled Action Switching Modules) was shown coordinating the joints of a robot leg and adapting its normal leg cycle to irregularities in the terrain. We also showed that the SCASM network can be implemented effectively on a simple micro-controller with little computational power. This video describes additional sensory connections that, when added to SCASM, generate elevator and searching reflexes. We also show for the first time an autonomous hexapod robot walking over irregular terrain using a SCASM network to control each of its six legs and a Cruse type network to control its gait using only on-board, simple micro-controllers.

A hexapod designed for wall climbing with a body joint and six 3-DOF legs can perform complex maneuvers such as sharp turns, making both interior and exterior transitions between vertical and horizontal surfaces, and traversing obstacles on both surfaces. This paper presents work toward the design and construction of the hexapod DIGbot, named for its utilization of distributed inward gripping (DIG) to generate adhesive forces. The biologically-inspired DIG approach allows robots to climb on surfaces of any orientation with respect gravity, including ceilings, or in zero gravity environments.

DAGSI Whegs is the latest generation of full size Whegs robots. The robot is designed for collaborative work with the Air Force Institute of Technology (AFIT) in SLAM with active feature recognition. Whegs vehicles use abstracted biological principles to navigate over irregular and varied terrain with little or no low level control. Torsionally compliant devices in the drive train of each wheel-leg allow its gait to passively adapt when climbing large obstacles or steep inclines. Whegs is similar to the RHex line of robots that preceded Whegs in that the foot motion of all 6 legs is circular, but it differs in many aspects: 3 leg-spokes versus 1, 1 drive motor vs. 6, leg rotation for steering instead of skid steering, passive gait adaptation vs. active gait control, and Whegs has a body joint.

Several recently-designed robots are able to scale steep surfaces using animal-inspired strategies for foot attachment and leg kinematics. These designs could be valuable for reaching high vantage points or for overcoming large obstacles. However, most of these robots cannot transition between intersecting surfaces. For example, our previous Climbing Mini-WhegsTMrobot cannot make a 90deg transition from a vertical wall up onto a flat horizontal surface. It is known that cockroaches bend their body to accomplish such transitions. This concept has been simplified to a single-axis body joint which allows ground-walking robots to cross uneven terrain. In this work, we examine the effect of a body joint on wall-climbing vehicles using both a kinematic simulation and two prototype Climbing Mini-WhegsTMrobots. The simulation accurately predicts that the better design has the body joint axle closer to the center of the robot than to the front wheel- legs for orthogonal exterior transitions for a wide range of initial conditions. In the future, the methods and principles demonstrated here could be used to improve the design of climbing robots for other environments.

For almost two decades, Holk Cruse's leg coordination method has been used as a control basis for generating gaits in legged robots. His stick insect inspired method has been successfully implemented for a number of robots such as Robot I and Robot II, the TUM Walking Machine, Tarry II, and BILL-Ant-p. However, some engineers have had difficulties implementing the controller when trying to select robust mechanism influence weights that are immune to variations in starting pose and leg speed. Additionally, the coordination method can be overwhelming for low- computation capable microcontrollers preferred for small, untethered mobile robots. The Biologically-Inspired Legged Locomotion-Low computation Emergent Gait System (BILL-LEGS) was developed as a solution to some of these issues. This method borrows heavily from Cruse's original design with some modifications that allow it to be implemented on small, autonomous legged robots using simple microcontrollers. This paper describes the BILL-LEGS method and its performance during simulation. Additionally, data are presented that show its robustness to mechanism weight selection and its generation of stable gaits, independent of leg starting positions and leg movement speeds.

Insects and geckos use claws and adhesive pads to negotiate both rough and smooth surfaces. Climbing robots have been designed to mimic various aspects of these and other biological systems to operate in specific vertical environments. Robots that adhere to the surface through suction cups, magnetic end-effectors, or adhesive pads can climb featureless, flat, or smoothly curved surfaces. Vortex-generating climbers do not require smooth surfaces. Robots have been designed with end-effectors that match specific features of the environment, such as peg-holes, handrails, climbing-wall footholds, and poles. Robots have also been fitted with insect-inspired spines to scale rough vertical surfaces.

Current autonomous and semi-autonomous robotic platforms are limited to functioning in highly structured environments such as buildings and roads. Autonomous robots that could explore and navigate rugged terrain and highly unstructured environments such as collapsed buildings would have large dividends in civilian and military applications. In this work, we present the next generation of Whegstrade robots, DAGSI Whegstrade, which has been completed and extensively field tested. Several innovations have made the robot more rugged and well suited to autonomous operation. Specifically, an actively controlled, passively compliant body joint has been tested in three different modes of operation to judge the usefulness of the mechanism. A two-dimensional dynamic simulation of the robot has also been constructed, and has been used to study the effects of weight distribution on obstacle climbing and to investigate future autonomous climbing strategies. Moving the center of mass forward allowed the robot to climb taller obstacles. DAGSI Whegstrade can climb rectangular obstacles as tall as 2.19 times the length of a leg.

Simulation of robots in a virtual domain has multiple benefits, including serving as a training tool for end users and serving as a tool for robot testing and development. USARSim (Unified System for Automation and Robot Simulation) is a simulation tool that is being used to accomplish these goals. It is based on the Unreal Tournament 2004 gaming engine, which approximates the physics of how a robot interacts with its environment. A family of robots that can benefit from simulation in USARSim are Whegstrade* robots. Developed in the Biorobotics Laboratory at Case Western Reserve University (CWRU), Whegstrade robots are highly mobile ground vehicles that use abstracted biological principles to achieve a robust level of locomotion, including passive gait adaptation and enhanced climbing abilities. This paper describes a Whegstrade robot model that was constructed and benchmarked in USARSim. The model was given the same kinds of physical characteristics found in real Whegstrade vehicles. With these traits in place, a validation study was performed for the simulation by comparing the rotational body motions of the virtual and real robot. Specifically, we examine the robotpsilas pitch and roll ranges and frequencies (found to be about 10 degrees to 12 degrees and 5.5 Hz respectively). By altering the simulation parameters in a physically relevant way, the virtual robotpsilas performance was moved to be more in line with these values.

Insights from biology have helped reduce the weight and increase the climbing ability of mobile robots. This paper presents Screenbot, see Fig. 1, a new 126 gram biologically-inspired robot that scales wire mesh substrates using spines. Like insects, it walks with an alternating tripod gait and maintains tension in opposing legs to keep the feet attached to the substrate. A single motor drives all six legs. Mechanisms were designed and tested to move the spines into and out of contact with the screen. After the spine engages the substrate, springs along the leg are compressed. The opposing lateral spring forces constitute a distributed inward grip that is similar to forces measured on climbing insects and geckos. The distributed inward gripping (DIG) holds the robot on the screen, allowing it to climb vertically, walk inverted on a screen ceiling and cling passively in these orientations.

Abstract—Mini-Whegs™, a power-autonomous vehicle that uses multi-spoke wheel-legs for locomotion, is able to climb vertical glass surfaces with several different wheel-leg designs. Adhesion to the glass is achieved using pressure sensitive adhesives. In this paper, high-speed video is used to compare the performance and contact area during steps of five passive foot designs. The contact area, when normalized by the leg length, may help explain the differences in performance between several designs. C I.

An approach to odor source localization with an aerial vehicle using the fusion of odor sensors, visual sensors, and airspeed sensors is presented. The motion of the tracking vehicle is decomposed into two components - a component normal to the wind direction and a component tangential to the wind direction. The tangential component is controlled with a strategy that moves upwind when odor is detected and moves gradually downwind when odor is lost. The normal component of velocity is controlled by two different algorithms. The first algorithm controls the rate of turning in the plane normal to the wind direction as a function of concentration. The second algorithm controls the rate of turning and the magnitude of the normal component of velocity as a function of the time derivative of concentration. Both algorithms display the potential to declare the location of an odor source in a three-dimensional space.

Robotic control systems inspired by animals are enticing to the robot designer due to their promises of simplicity, elegance and robustness. While there has been success in applying general and behaviorally-based knowledge of biological systems to control, we are investigating the use of control based on known and hypothesized neural pathways in specific model animals. Neural motor systems in animals are only meaningful in the context of their mechanical body, and the behavior of the system can be highly dependent on nonlinear and dynamic properties of the mechanical part of the system. It is therefore reasonable to believe that to reproduce behavior, the physical characteristics of the biological system must also be modeled or accounted for. In this paper we examine the performance of a robotic system with three types of muscle model: null, piecewise-constant, and linear. Results show that adding very simple models of muscle properties at a single joint cause marked improvement in the performance of a neurally-based step generator for a 3-degree-of-freedom robotic leg.

Biological inspiration has a history of advancing the field of robotics. Increasingly, robots are also being used in the modeling of biological systems. In this paper, we use recorded cockroach electromyograms (EMGs) to drive artificial muscle (braided pneumatic actuator) activation and thereby robot joint motion, in an effort to model the transformation from EMG to behavior in the animal. A muscle activation model was developed that transforms EMGs recorded from behaving cockroaches into appropriate commands for the robot. The transform is implemented by multiplying the EMG by an input gain thus generating an input pressure signal, which is used to drive a one-way closed-loop pressure controller. The actuator then can be modeled as a capacitance with input rectification. The actuator exhaust valve is given a leak rate, making the transform a leaky integrator for air pressure, which drives the output force of the actuator. We find parameters of this transform by minimizing the difference between the robot motion produced and that observed in the cockroach. Results from evaluation on reduced-amplitude cockroach angle data strongly suggest that braided pneumatic actuators can be used as part of a physical model of a biological system.

Current Mars exploration and science is limited to orbiters and areas close to original rover landing sites. Most of the places of geological interest lay many kilometers outside of suitable landing sites. In-situ resources such as wind can enable rovers to travel great distances on Mars while using little internal power. In this paper, a dynamic model of an individual wind driven rover is used to enhance a stochastic simulation of multiple rovers traversing the Martian environment. The results from this simulation support the claim that a group of rovers equipped with minimal control mechanisms or internal energy sources can autonomously disperse and explore Mars.

We previously presented a remote-controlled robot, Climbing Mini-Whegstrade, which scales vertical glass walls using passive compliant feet on simple rotating wheel-legs [1]. With a single drive motor, the legs of the robot press the feet against the glass, then gradually peel them away, mimicking the foot motions observed in insects. With feet made of scotch tape, the robot was able to walk on glass walls and ceilings and transition between surfaces intersecting at interior angles. This paper demonstrates that using passively compliant feet on simple rotating wheel-legs a robot can apply adhesive feet, spines, and Velcro in order to climb various steep substrates.

A new strategy is developed for tracking an odor plume in an environment where wind is present. The strategy is inspired by the mechanisms that animals use to orient to stimuli. A male moth counter-turns horizontally and vertically across the wind while tracking a pheromone plume. The inter-turn duration, or the amount of time between turns, is about 500 milliseconds on average in both directions. This observation has lead to the development of odor tracking algorithms that use inter-turn timers to control when to turn in both directions. The algorithm presented in this work takes a different approach. The new algorithm controls the rate of turning of the tracking vehicle in a plane normal to the wind direction. Simulation results demonstrate that counter-turning can be achieved in both directions without the use of inter-turn timers. Also, the estimated odor source location approaches the true source location as time progresses

The current generation of micro air vehicles (MAVs) has reached a plateau in its utility, due to reliance on single-mode locomotion. A micro vehicle capable of both aerial AND terrestrial locomotion would enjoy great utility in first responder and reconnaissance applications. To this end, BioRobots, LLC, University of Florida (UF), Case Western Reserve University, and Naval Postgraduate School (NPS) have undertaken the development of MMALV, the Morphing Micro Air-Land Vehicle. MMALV combines the UF-MAV flexible wing technology with Mini-Whegs terrestrial running gear, developed at Case. Two generations of MMALV have been developed that are capable of flying, landing, walking, and regaining flight by walking off a two-story building. To our knowledge, MMALV is the only vehicle of its size that integrates all of these functions.

A robot, Robot V (Ajax) has been constructed based on the death head cockroach, Blaberus discoidalis. In an attempt to further take advantage of the neuromechanics of the animal, actuators with muscle-like properties have been employed that demonstrate a superior force to weight ratio over conventional actuation devices. Although it is not feasible to capture the entire range of motion displayed by the animal (seven degrees of freedom per leg), research has shown that twenty-four degrees of freedom provide a sufficiently close approximation for agile walking and climbing. The fifteen kilogram robot has an offboard power source and control system

Many untethered mobile robots require an operator's vision and intelligence for guidance and navigation. Animals and insects, however, use sensory systems such as hearing, and tactile inputs to move autonomously through their environment. This paper discusses the implementation of a simple binaural sensory pod using an ultrasonic emitter and two receivers on a mobile robot that employs legged-style locomotion. A series of obstacle avoidance behaviors programmed onto a microcontroller allow the robot is to successfully navigate a cluttered environment both semi-autonomously and autonomously.

Many untethered mobile robots require an operator's vision and intelligence for guidance and navigation. Animals and insects, however, use sensory systems such as hearing, and tactile inputs to move autonomously through their environment. This paper discusses the implementation of a binaural sensory pod using an ultrasonic emitter and two receivers on a mobile robot that employs legged-style locomotion. A series of obstacle avoidance behaviors programmed onto a microcontroller allows the robot is to successfully navigate a cluttered environment both semi-autonomously and autonomously

Two simple three-dimensional moth inspired odor tracking algorithms, Counter-turner and Modified counter-turner, were tested on a robotic platform. The Counter-turner uses the plume edge to modify the timing of the crosswind movements, while the Modified counter-turner uses the plume centerline. Both algorithms shows some success in tracking the plume to it’s source. In addition, flight tracks show promise in mimicking the flight tracks observed in biological experiments with the moth Manduca. Sexta.

This paper describes the latest additions to the Mini-Whegs™ series of small robots. These new robots are fully enclosed, measure 9 to 10 cm long, and range in weight from 90 g to 190 g. Mini-Whegs™ 7 weighs less than 90 g, but can run at over three body-lengths per second and surmount 3.8 cm high obstacles. The most recent iteration, Mini-Whegs™ 9J, incorporates fully independent running and jumping modes of locomotion. The controllable jumping mechanism allows it to leap as high as 18 cm.

Through the use of mechanical, actuated antennae a biologically-inspired robot is capable of autonomous decision-making and navigation when faced with an obstacle that can be climbed over or tunneled under. Vertically-sweeping mechanical antennae and interface microcontrollers have been added to the Whegs ™ II [1] sensor platform that allow it to autonomously sense the presence of, and successfully navigate a horizontal shelf placed in its path. The obstacle is sensed when the antennae make contact with it, and navigation is made possible through articulation of the Whegs ™ II body flexion joint.

A sensor platform has been developed that is capable of both aerial and terrestrial locomotion, as well as transitioning between the two. The morphing micro air-land vehicle (MMALV) implements biological inspiration in both flying and walking. MMALV integrates the University of Florida's micro air vehicle (MAV) technology with the terrain mobility of Mini-Whegs/spl trade/. Fabricated of lightweight carbon fiber, the UF-MAV employs a flexible wing design to achieve improved stability over other MAVs of similar size. Mini-Whegs/spl trade/ employs the patented (pending) wheel leg running gear that makes the Whegs/spl trade/ and Mini-Whegs/spl trade/ line of robots fast, agile, and efficient. MMALV has a 30.5cm wingspan, and is 25.4cm long. Terrestrial locomotion is achieved using two independently controlled wheel legs, which are differentially actuated to perform turning. The vehicle successfully performs the transition from flight to walking. Furthermore, MMALV is capable of transitioning from terrestrial to aerial locomotion by walking off a structure of only 20 feet. A wing retraction mechanism improves the portability of the vehicle, as well as its terrestrial stealth and ability to enter small openings.

Abstract – The ability to walk on surfaces regardless of the presence or direction of gravity can significantly increase the mobility of a robot for both terrestrial and space applications. Insects and geckos can provide inspiration for both novel adhesive technology and for the locomotory mechanisms employed during climbing. For this work, Mini-Whegs™, a small quadruped robot that uses wheel-legs for locomotion, was altered to explore the feasibility of scaling vertical surfaces using compliant, adhesive feet. Modifications were made to reduce its weight, and its legs were redesigned to enable its feet to better attach and detach from the substrate, mimicking homologous actions observed in animals. The resulting vehicle is selfcontained, power-autonomous, and weighs only 87 grams. Using pressure-sensitive tape, it is capable of walking up a vertical surface, walking upside-down along an inverted surface, and transitioning between orthogonal surfaces. Index Terms – Biologically inspired robotics, wall-climbing robots, adhesive-based climbing vehicles.

Implementing cockroach footpaths using simple leg mechanisms results in cockroach-like body motion in a hexapod robot called "mecharoach". The mecharoach utilizes rotary input four-bar mechanisms to achieve legged locomotion while being powered by only one DC motor. MechaRoach can walk at one body length per second and can climb a barrier 70% its height. High-speed video analysis of walking cockroaches and mecharoach indicates that mecharoach exhibits body motion during walking that is very similar to the cockroach. This suggests that footpaths and stepping patterns play a significant role in an animal or robot's overall body motion.

A mobile autonomous robot capable of tracking an odor plume to its source can be used to locate hazardous material spills or leaks. To test plume tracking strategies in a laboratory environment, a robotic platform consisting of a linear Cartesian robotic gantry mounted inside a wind tunnel with a mobile floor has been designed. A plume of ionized air is created by an ion detector installed in the wind tunnel. A two-dimensional plume tracking strategy based on the behavior of the tobacco hornworm moth Manduca sexta is implemented and tested. It is discovered that a plume tracking algorithm can be implemented with the robotic platform almost as easily as in simulation.

Abstracting cockroach locomotion principles with reduced actuation can lead to a simple yet effective cockroach-like vehicle able to traverse irregular terrain. One such hexapod robot is Whegs VP, which achieves a cockroach-like nominal tripod gait using only a single DC motor. Whegs VP uses compliant mechanisms in its axles to passively adapt its gait to the terrain such that it can climb obstacles 175% of its leg height. High speed video analysis of walking cockroaches and Whegs VP illustrates that Whegs VP walks with cockroach-like body motions. The experiments indicate that stepping patterns play a major role in an animal's or robot's overall body motions.

A new human-machine interface is introduced for "hands-free" tele-operation of mobile robots. This interface consists of tracking tongue movement by monitoring changes in airflow that occur in the ear canal. Tongue movements within the human oral cavity create unique, subtle pressure signals in the ear that can be processed to produce commands signals in response to that movement. Once recognized, said movements can in turn be used in for robotic tele-operation. The complete strategy is tested on 4 tongue actions: touching the tongue to the left and right corners of the mouth, and to the top and bottom center of the mouth. Through extensive experiments, it is shown that the pressure signals due to tongue movements are distinct and can be detected with over 97% accuracy. A case study to control the Whegs II robotic platform has specifically been investigated. Based on simulation results, it is concluded that this unique strategy will make hands-free robotic tele-operation a practical reality.

Applying abstracted biological locomotion principles with reduced actuation can result in an energetic vehicle with greater mobility because a vehicle with the fewest number of motors can have the highest power to mass ratio. One such hexapod is Whegs II, which benefits from abstracted cockroach locomotion principles and has just one motor for propulsion. Similar to Whegs I, it nominally runs in a tripod gait and passive mechanisms enable it to adapt its gait to the terrain. One of the drawbacks of Whegs I is that it cannot change its body posture. Cockroaches pitch their bodies up in anticipation of climbing a step to enable their front legs to reach higher. They also flex their bodies down while climbing to permit their front legs to maintain contact with the substrate. A bidirectional servo-driven body flexion joint has been implemented in Whegs II to accomplish both of these behaviors. It is shown to be highly mobile and energetic.

This paper describes novel highly mobile small robots called "mini-whegs" that can run and jump. They are derived from our larger whegs series of robots, which benefit from abstracted cockroach locomotion principles. Key to their success are the three spoked appendages, called "whegs", which combine the speed and simplicity of wheels with the climbing mobility of legs. To be more compact than the larger whegs vehicles, mini-whegs uses four whegs in an alternating diagonal gait. These 9 cm long robots can run at sustained speeds of over 10 body lengths per second and climb obstacles that are taller than their leg length. They can run forward and backward, on either side. Their robust construction allows them to tumble down a flight of stairs with no damage and carry a payload equal to twice their weight. A jumping mechanism has also been developed that enables mini-whegs to surmount much larger obstacles, such as stair steps.

Although braided pneumatic actuators are capable of producing remarkable forces compared to their weight, they have seen little mainstream use. One of the reasons is their relatively short fatigue lives at high pressure. By improving the manufacturing techniques, the actuator lifetime was extended by nearly an order of magnitude. Another concern is that their response times may be too long for the control of legged robots. However, the frequency response of these actuators was found to be similar to that of human muscle.

A device that could locomote through curving and tortuous spaces would find many applications in medicine and in industry. Invertebrates such as earthworms and leeches can solve this problem using peristaltic locomotion. We describe a device consisting of three braided pneumatic actuators in series that can successfully locomote peristaltically. The device can locomote forwards and backwards in elevated and curving tubes, and with a plastic sheath around it.

Biological inspiration can be used to improve the mobility of vehicles, even those that are simplified and use current technology. One such hexapod robot called Whegs I is described. Mechanisms in its design permit it to move over various terrains and climb over small obstacles in a manner similar to a cockroach. It uses one motor for propulsion and two small servos for steering. Its appendages, called whegs, consist of three evenly spaced spokes. Passive compliance in its axles permits its nominal tripod gait to adapt to irregular terrain and evolve to co-activation for climbing. Basic locomotion control is implemented in its, mechanical design. A benefit of this mechanical simplicity is that its control system is also simplified. Drawbacks to the simplifications include the inability to change the body's posture and decrease overhead clearance. Some of these problems will be addressed in future versions without compromising the basic design.

Describes the development of an autonomous hybrid micro-robot that uses legs for propulsion and support of the rear half of the body and uses a pair of wheels for support of the front half. McKibben artificial muscles actuate the legs and the compressed air that activates the actuators is generated by an on-board power plant comprising a pair of lithium batteries powering a gear motor driven air compressor. The control is also onboard in the form of a PIC that controls the actuators through four three-way valves that each consists of a pair of MEMS devices.

A four-DOF planar robotic leg actuated with McKibben artificial muscles was designed, constructed, and controlled. Both position and passive stiffness were independently controllable at each joint. The tunable passive stiffness properties of the actuators provided stable, forward walking for the robot. A benefit of passive joint stiffness is energy efficiency. Results indicate that the leg may be capable of walking on a horizontal plane with its control valves off 90% of the time. The muscle-like properties of these actuators, including high strength-to-weight ratio, tunable passive stiffness, and self-limiting force output, make them well suited for legged robots.

Braided pneumatic actuators exhibit non-linear force-length properties grossly similar to muscle, and have a high strength-to-weight ratio. These properties make them desirable for legged robots. The work emphasizes understanding the actuator properties for later use in simulation and control of legged robots. Static and dynamic mathematical models for the actuators are reported and verified through testing and simulation. In addition, a dynamic air flow model modulated by a solenoid valve was developed to provide modular actuation subroutines for simulation.

The legs of animals and walking vehicles are subject to substantial changes in loading in climbing over obstacles. Sense organs (campaniform sensilla) on cockroach legs detect these loads through strains in the exoskeleton. Signals that might be sent by the sense organs during climbing were predicted by applying forces to a finite element model of the leg in directions determined from kinematic studies. The model included an accurate, three-dimensional reconstruction of the leg segment (trochanter) that contains an array of these sensors. Calculated strains generated at different phases of climbing suggest that some groups of sensors in the front leg, that show little activity in walking, are strongly activated in climbing. These groups could provide signals to aid in adapting walking patterns to the changing forces encountered in climbing.

We introduce an evolutionary flight path planning algorithm capable of mapping paths for free-flying vehicles functioning under several aerodynamic constraints. An air-to-ground targeting scenario was selected to demonstrate the algorithm. The task of the path planner was to generate inputs flying a munition to a point where it could fire a projectile to eliminate a ground target. Vehicle flight constraints, path destination, and final orientation were optimized through fitness evaluation and iterative improvement of generations of candidate flight paths. Evolutionary operators comprised of one crossover operation and six mutation operators. Several cases for air-to-ground vehicle targeting have been successfully executed by the evolutionary flight path planning algorithm under challenging initial conditions. The results demonstrate that evolutionary optimization can achieve flight objectives for air vehicles without violating limits of the aircraft.

A target-seeking system for autonomous munitions in the endgame stage of flight is developed based upon a neural network model of the cockroach escape reflex. Despite significant differences in objectives, certain aspects of the cockroach escape response are consistent with desired characteristics of a target seeking system. An evolutionary target-seeking algorithm was generated to gather data to train the neural net target-seeking system. Targeting data was generated through intensive offline computing, which the target-seeking reflex was trained to reproduce on-line instantly. A linear quadratic regulator (LQR) autopilot executes reflexive guidance commands. With the trained target-seeking system installed on a candidate air to-ground munition, simulations show that the reflex may react to strike targets very quickly. Context dependency was demonstrated through the actions of the reflex striking targets moving on rapidly changing, evading, and unpredictable trajectories, as well as through false and disruptive sensor data.

Our goal is to develop an autonomous robot that will fit within a two-inch cube and will provide locomotion by walking and jumping. The robot is based-on the kinematics of a cricket. It is actuated by braided pneumatic actuators with compressed air provided by an on-board compressor. The air can be distributed by an array of actuated MEMS valves. A neural network is used to control the robot, and it can be implemented in an analog VLSI circuit. The joint angles can be measured using MEMS joint angle sensors that are based on biological sensors studied in the cricket and other insects.

We illustrate a methodology for modeling and analyzing flexible feeders using generalized semi-Markov process (GSMP) models. Working through the simple case consisting of a single part being fed on a flexible feeder, we show how the throughput of the system may be obtained by both GSMP simulation and analytical techniques for GSMP models. Further, we demonstrate the predictive capability of such models. This is accomplished by generating and validating a model of the system feeding three distinct part types (at the same time) and then modifying the model to allow other feeding scenarios to be predicted. These scenarios include the effect of feeding the parts in a specific order, the effect of using a robot with different speed capabilities, and the effect of using a different-sized presentation conveyor. We validate the predictions with physical testing.

This paper describes the kinematic analysis of two different cricket locomotion modalities, and the use of these data in a dynamic simulation to combine and simplify the insect's complex three-dimensional movements. The results of this simulation will then become the input to the design and control of a microrobot capable of mimicking the walking and jumping behaviors of the cricket.

The monopod hopper described fits into a cube that is 5 cm on a side, is autonomous, and is designed to be statically stable and passively dynamically stable. Hopping is achieved through the excitation of a spring-mass system at its resonant frequency. Simulations were extensively used to finalize the design, before construction of the robot. The hopper, although having no active directional control, is able to climb steps up to 1 mm, travel at a rate of 1.5 body lengths per second for an average of over 225 cm before deviating significantly from its original course, and can operate up to 45 min before depleting the energy stored in the batteries.

Summarizes results of a five-year, multi-disciplinary, university-industry collaborative effort investigating design issues in agile manufacturing. The focus of the project is specifically on light mechanical assembly, with the demand that new assembly tasks be implementable quickly, economically, and effectively. Key to achieving these goals is the ease of equipment and software reuse. Design choices for both hardware and software must strike a balance between the inflexibility of special-purpose designs and the impracticality of overly general designs. We review both our physical and software design choices and make recommendations for the design of agile manufacturing systems.

Flexible parts feeding techniques have begun to gain industry acceptance. However, one barrier to effective flexible feeding solutions is a dearth of knowledge of the under lying dynamics involved in flexible part feeders. The paper presents the results of testing the CWRU flexible parts feeder. Data was collected for extended periods while feeding a variety of parts. The data was examined to determine throughput and statistical properties. In addition, tests were performed to examine other aspects of the system. A new metric for specifying the throughput of vision-based flexible feeders is presented, interesting system phenomena are examined, and a statistical analysis of the data is performed.

This paper describes guidelines for the design of grippers for use in modular manufacturing workcells. Gripper design is an important and often overlooked aspect of the design of a complete assembly system. Here, we present guidelines which can be applied to a wide variety of grippers and are divided into two major categories: those that improve system throughput and those that increase system reliability. Designs of several grippers, currently being used in a modular manufacturing workcell, are presented as examples of the application of the guidelines to real world problems.

A rough terrain locomotion controller for an eight-legged demining robot built by K/sup 2/T, Inc. is presented. The method takes inspiration from the behavior of biological organisms to create a robust yet computationally simple controller. Included is a brief description of mechanism based gait control and insect-inspired reflexes for rough terrain locomotion which were previously used to control a hexapod robot with great success. This method is then applied to develop a locomotion controller for the K/sup 2/T crab-like demining robot. In simulation, the resulting controller causes the robot to display successful rough terrain navigation ability including walking over irregular terrain, traversing obstacles on the order of half the tibia length, traversing sparse terrain, and crossing ditches, all without complex sensing or terrain mapping.

The design of a biomimetic actuation system which independently modulates position and net stiffness is presented. The system is obtained by antagonistically pairing contractile devices capable of modulating their rate of geometric deformation relative to the rate of deformation of a passive elastic storage element in series with the device's input source. A mechanical model is developed and the properties of the device are investigated. The local properties of the system are then investigated via Lyaponov's linearization method.

Describes the posture controller for a new cockroach-like hexapod robot developed in the Bio-Robotics Laboratory at Case Western Reserve University. The posture controller is based upon the virtual model control scheme and the problem of redundant kinematics is solved using an optimization approach. It does not just control static posture, but is the major component of a future locomotion controller. The robot has complex, animal-like kinematics with 24 degrees of freedom, yet the controller effectively manages its posture despite large perturbations. The algorithm is also computationally efficient.

Any device that moves by actuating several multi-segmented legs must solve fundamental problems in mechanics and control regardless of whether that device is made out of living tissue or metal. With this in mind, we believe that advances can be made both in the design of legged robots and in understanding how legged animals locomote by working on these issues in tandem. This basic philosophy has led us to build a hexapod robot with kinematics that are remarkably similar to those of the death head cockroach Blaberus discoidalis . This eff ort has required us to make detailed neurobiological and kinematic observations of cockroaches walking on a treadmill and climbing over barriers. The data acquired in this way were then input to our dynamic simulation tool to determine mechanically accurate parameters for the design of the robot. The resulting vehicle captures the cockroach kinematics so well that issues that are being addressed in controlling it are providing important notions regarding the neural control of locomotion in the animal. Thus, the project has led to benefits in both directions. Biological data inspired the initial design of the robot, while engineering eff orts in control are inspiring further neurobiological experiments in animal locomotion.

This paper describes the design and implementation of a flexible parts feeding system. While flexibility encompasses every part of the workcell design, including hardware and control software, the ability to feed parts in a wide variety of sizes and shapes is crucial. Conventional feeding methods, such as vibratory bowl feeders, are not practical for flexible workcells because of their specialized nature. This system is composed of three conveyors working together. The first conveyor is inclined and lifts parts from a bulk hopper in a quasi-singulated manner. Parts fall from the first conveyor onto the second, horizontally mounted, conveyor. An underlit window at the end of the second conveyor presents a silhouette image of the parts to a vision system. After the pose of a part has been determined, a robotic arm is used to acquire it. Parts which are in unfavorable orientations or are overlapping are returned to the bulk hopper by a third conveyor. Guidelines for part design which improve the feeding system's performance are also presented.

A crash avoidance system for automobiles is developed based upon a distributed network of artificial neurons that mimic the neural organization of the escape system in the American cockroach. The cockroach escape circuit is shown to be an excellent source of inspiration for the development of a collision avoidance system. The crash avoidance system is implemented in an artificial neural network which is trained off-line, but then is shown to produce real-time performance. A collision avoidance scheme which makes use of a crash alarm strategy is developed for training the neural network. A dynamic model of a four-wheeled vehicle with front wheel steering and realistic performance constraints is used to test the crash avoidance system. Simulation results show that the well-trained neural network causes successful, reflexive crash avoidance behaviors in a dynamic environment without a priori information.

An agile workcell has been developed for light mechanical assembly in collaboration with industrial sponsors. The workcell includes multiple Adept robots, a Bosch conveyor system, multiple flexible parts feeders at each robot's workstation, CCD cameras for parts feeding and hardware registration, and a dual VMEbus control system. Our flexible pairs feeder design uses multiple conveyors to singulate the parts and machine vision to locate them. Specialized hardware is encapsulated on modular grippers and modular worktables which can be quickly interchanged for assembly of different products. Object-oriented software (C++) running under VxWorks, a real-time operating system, is used for workcell control. An agile software architecture was developed for rapid introduction of new assemblies through code re-use. A simulation of the workcell was developed so that controller software could be written and tested off-line, enabling the rapid introduction of new products.

This paper describes the design and simulation of a cockroach-like hexapod robot which is under construction for the purpose of testing control principles which are being extracted from the cockroach. The cockroach was chosen because of its remarkable running and climbing capabilities and because much is known about its biomechanics and control. The robot is designed with five, four, and three degrees of freedom in the front, middle and rear legs, respectively, to permit it to mimic the different functions of cockroach legs. Pneumatic cylinders actuate each joint and provide opposing muscle-like forces to actuate the joints. Pulse-width modulation controls the actuators with the necessary smoothness and precision. A dynamic simulation has been developed to predict loads on the structure and the required joint torques.

This paper introduces a design for agile manufacturing workcells intended for light mechanical assembly of products made from similar components (i.e. parts families). We define agile manufacturing as the ability to accomplish rapid changeover from the assembly of one product to the assembly of another product. Rapid hardware changeover is made possible through the use of robots, flexible part feeders, modular grippers and modular assembly hardware. The flexible feeders rely on belt feeding and binary computer vision for Dose estimation. This has a distinct advantage over non-flexible feeding schemes such as bowl feeders which require considerable adjustment to changeover from one part to another. Rapid software changeover is being facilitated by the use of a real-time, object-oriented software environment, modular software, graphical simulations for off-line software development, and an innovative dual VMEbus controller architecture. These agile features permit new products to be introduced with minimal downtime and system reconfiguration.

We present fully distributed neural network architecture for controlling the locomotion of a hexapod robot. The design of this network is directly based on work on the neuroethology of insect locomotion. Previously, we demonstrated in simulation that this controller could generate a continuous range of statically stable insect-like gaits as the activity of a single command neuron was varied and that it was robust to a variety of lesions. We now report that the controller can be utilized to direct the locomotion of an actual six-legged robot, and that it exhibits a range of gaits and degree of robustness in the real world that is quite similar to that observed in simulation.

The robustness of a distributed neural-network controller for locomotion based on insect neurobiology has been used to control a hexapod robot. The robustness of the controller is investigated experimentally. Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.>