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.

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.

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.

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.

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.

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.

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.

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.

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 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

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.