Exploring and navigating in extreme environments, such as caves, oceans, and planetary bodies, are often too hazardous for humans, and as such, robots are possible surrogates. These robots are met with significant locomotion challenges that require traversing a wide range of surface roughnesses and topologies. Previous locomotion strategies, involving wheels or ambulatory motion, such as snake platforms, have success on specific surfaces but fail in others, which could be detrimental in exploration and navigation missions. In this article, we present a novel approach that combines snakelike robots with an Archimedean screw locomotion mechanism to provide multiple, effective mobility strategies in a large range of environments, including those that are difficult to traverse for wheeled and ambulatory robots. This work develops a robotic system called ARCSnake to demonstrate this locomotion principle and tested it in a variety of different terrains and environments in order to prove its controllable, multidomain, navigation capabilities. These tests show a wide breadth of scenarios that ARCSnake can handle, hence demonstrating its ability to traverse through extreme terrains.

This paper presents a reactive control framework for robotic bipedal running over random discrete terrain using a shift-invariant funnel library that can be composed into motion plans. The main contribution of the paper is the formalization of the funnel library and the introduction of a receding-horizon reactive planner that utilizes this funnel library. The proposed controller generates a robust motion plan on the fly, without the need for predefined footholds or center of mass trajectory, via sequential-composition of pre-computed funnels. The proposed method utilizes three layers of robustness: high-level reactive planning, low-level robust control, and funnel-based, pre-computed, performance guarantees. For clarity, we provide a detailed example, using the 5 degrees-of-freedom sagittal biped model. We demonstrate in simulation the ability of the framework to overcome uncertainty in sensing and model parameters.

This paper investigates a burrowing robot that can maneuver and steer while being submerged in a granular medium. The robot locomotes using an internal vibro-impact mechanism and steers using a rotating bevel-tip head. We formulate and investigate a non-holonomic model for the steering mechanism and a hybrid dynamics model for the thrusting mechanism. We perform a numerical analysis of the dynamics of the robot's thrusting mechanism using a simplified, orientation and depth dependent model for the drag forces acting on the robot. We first show, in simulation, that by carefully tuning various control input parameters, the thrusting mechanism can drive the robot both forward and backward. We present several experiments designed to evaluate and verify the simulative results using a proof-of-concept robot. We show that different input amplitudes indeed affect the direction of motion, as suggested by the simulation. We further demonstrate the ability of the robot to perform a simple S-shaped trajectory. These experiments demonstrate the feasibility of the robot's design and fidelity of the model.

Robotic manipulators can be found today in most industries, from autonomous warehouses to advanced assembly lines in factories. Most of these industrial robots are characterized by having non-flexible and highly rigid links. In dense and complex environments these manipulators require many degrees of freedom (DOFs) which complicates the mechanical structure of the manipulator, as well as the control and path planning algorithms. In this work we present a minimalistic approach to reduce the number of active DOFs by using non-rigid, Hyper-Flexible Manipulators (HFM). We introduce a dynamic model of the HFM as well as a control scheme to bring the end-effector to a desired position from known initial configuration. Finally, we present experiments that support the analytic part and simulative results of this paper.

Layout of the interior works during building construction is time consuming and error prone. Given the cost involved, both for initial layout and for later rework where errors occur, researchers have sought to automate the layout task. Some have adopted marker-less augmented reality methods using heads-up displays or cameras, and others have proposed robots capable of marking out the works. The former encumber the workers, the latter are expensive to set up and are sensitive to site conditions, and neither has yet achieved the required accuracy. In this paper, we propose a more efficient approach to project relevant information from a building information model (BIM) onto the construction surface, directly augmenting the construction site with the design information. This is done using a portable system consisting of a 2-D laser scanner, an angled adjustable projector, and a camera. The system localizes itself within the already built outer walls using the laser scanner and the BIM model using a method derived from robotic mapping; it calibrates the projection correction parameters (keystone correction) using image analysis; and it projects the information with the angled projector. Testing results showed that the localization was accurate within a few millimeters and less than 3°, and the final projected image's error was approximately 1 cm. Initial calibration requires less than 1 min and does not require specialist skills. The system automates the layout task, preserves accuracy, and can provide rich model information on any interior surface.

By bonding micron-thin polymer layers with an electrically conductive layer, we can utilize the bi-metal effect to create a soft, thin, electrically-activated thermal actuator (ETA), which can be used in printed soft robots. Using ETAs have shown quite remarkable potential in previous works. However, to reveal their true capabilities, we propose to utilize a multi-layered ETA. In this research, we analytically model the actuator for both the bi-, and more importantly, tri-layer ETAs and analyze their behavior. We develop a simple intuitive model to better explain the benefits of the tri-layer actuation and to estimate the optimal design parameters. We verify the models by conducting an experiment to measure the curvature change for different third layer thicknesses. The experiments show a significant improvement in performance of the tri-layer actuators and display a good fit between the simplified analytic model and the full model.

This paper describes a simple control scheme for the two-legged dynamic climbing robot, the ParkourBot. Inspired by the swing leg retraction (SLR) method used on running robots, we propose to implement an SLR controller that does not require an actual apex crossing event as an initiator. The familiar SLR control for running is initiated when the center of mass (CoM) of the robot reaches the apex of its trajectory. Often, dynamic climbing gaits do not reach an apex. We therefore define an alternative initiator named, the virtual apex. We evaluate two simple models, the conservative spring loaded inverted pendulum (SLIP) model, and the more realistic non-conservative SLIP model. We show, in simulation, that using SLR we are able to stabilize and control the otherwise unstable conservative SLIP model. We also show, that using the SLR significantly increases the robustness of the non-conservative SLIP model. Finally, we validate our results through experiments on the ParkourBot climbing robot.

This paper investigates a simple swimming mechanism, which comprises two concentric bodies and two passive flaps. The mechanism propels itself forward by oscillating its inner body in a symmetric fashion using a single actuator. The paper starts by using a simple model to investigate the dynamics of the robot and to simulate its motion. Next, we simulate various design parameters and conclude that some parameters can improve the performance of the swimming robot. We conclude with a proof-of-concept prototype that is capable of swimming similar to the predicted model. Moreover, by using an asymmetric input, the mechanism is able to rotate in various curvatures. The combination of these forward and rotational gaits can be used to stabilize the robot onto a desired trajectory.

The Spring-Loaded Inverted Pendulum (SLIP) is a widely used model for the description of humans and animals running motion. The SLIP model is, however, sensitive to impact angle for various terrain heights. One known method for increasing the model's robustness to terrain changes is the Swing Leg Retraction (SLR) method. Despite its popularity, an analytic formulation of this method has yet been provided. In this work, using an instantaneous stance phase assumption, we present the increase in robustness of the swing method. This analysis provides a way to isolate the optimal parameters of the SLR. We validate these optimal parameters in simulations and proof-of-concept experiments in a planar environment.

The ParkourBot climbs in a planar reduced-gravity vertical chute by leaping back and forth between the chute's two parallel walls. The ParkourBot is comprised of a body with two springy legs and its controls consist of leg angles at touchdown and the energy stored in them. During flight, the robot stores elastic potential energy in its springy legs and then converts this potential energy in to kinetic energy at touchdown, when it “kicks off” a wall. This paper describes the ParkourBot's mechanical design, modeling, and open-loop climbing experiments. The mechanical design makes use of the BowLeg, previously used for hopping on a flat ground. We introduce two models of the BowLeg ParkourBot: one is based on a nonzero stance duration using the spring-loaded inverted pendulum model, and the other is a simplified model (the simplest parkour model, or SPM) obtained as the leg stiffness approaches infinity and the stance time approaches zero. The SPM approximation provides the advantage of closed-form calculations. Finally, predictions of the models are validated by experiments in open-loop climbing in a reduced-gravity planar environment provided by an air table.

Autonomous capabilities for manipulating randomly piled objects may enhance current methods of path planning and open a new field of development for mobile manipulation and Urban Search And Rescue (USAR) robotics. This paper introduces the challenge of achieving such manipulation capabilities and as a first step presents three algorithms, including a proposed novel solution, for the selection of objects to remove from a pile. The proposed algorithm determines a removability rank for each object according to the degree of its encapsulation within other objects. Using the contact vectors of the examined object, it is possible to obtain the motions that will not violate the object's unilateral contact constraints. The removability rank of the object is proportional to the union of all such motions. All algorithms were tested in simulation in full and partial knowledge modes, and evaluated on a physical robot with a simple manipulator and sensor. This work contributes: the introduction of an important autonomous manipulation challenge, the solution of which will be useful in the field of manipulation in general and USAR in particular; a specific novel algorithm for the construction of disassembly plans for piled objects; and an experimental evaluation of three algorithms targeted at such construction.

This video elaborates on a new active and controllable over-tube addition to the highly articulated robotic probe; the HARP. This over-tube allows the current HARP mechanism to double its overall length and allows it to perform more complex tasks. We explain the design concept of the current HARP and the novel over-tube mechanism and show two proof-of-concept experiments demonstrating the use of the active over-tube.

The ParkourBot is an efficient and dynamic climbing robot. The robot comprises two springy legs connected to a body. Leg angle and spring tension are independently controlled. The robot climbs between two parallel walls by leaping from one wall to the other. During flight, the robot stores elastic energy in its springy legs and automatically releases the energy to "kick off" the wall during touch down. This paper elaborates on the mechanical design of the ParkourBot. We use a simple SLIP model to simulate the ParkourBot motion and stability. Finally, we detail experimental results, from open-loop climbing motions to closed-loop stabilization of climbing height in a planar, reduced gravity environment.

This paper investigates a novel minimalistic mechanism that ascends tubes. The mechanism is comprised of only a rigid body, two O-rings, and a motor rotating an eccentric mass. We describe the underlying locomotion principle of rocking and jamming, without the use of special bristles or spines, and demonstrate the robustness of this mechanism.

This paper investigates a novel mechanism, called DSAC for Dynamic, Single Actuated Climber, which propels itself upwards by oscillating its leg in a symmetric fashion using a single actuator. This mechanism achieves dynamic, vertical motion while retaining simplicity in design and control. We explore the local orbital stability of the DSAC mechanism. We use the Poincaré map method with a well chosen Poincaré section to simplify the problem by reducing the dimension of the Poincaré map to 3-dimensions. We find the stable regions while varying the controls input and some of the mechanism's parameters. Moreover, in response to a continuous change in a parameter of the mechanism, the symmetric and steady stable gait of the mechanism gradually evolves through a regime of period doubling bifurcations.

This video shows the investigation of a novel minimalistic, dynamic climbing robot which can climb up tubes of different shapes using a simple dc motor. The motor moves an eccentric mass in a constant velocity. The location of the eccentric mass relative to the contact point determines the stability and the direction of the climbing motion. We present the analysis of this mechanism, simulation and experimental results.

A climbing robot mechanism is introduced, which uses dynamic movements to climb between two parallel vertical walls. This robot relies on its own internal dynamic motions to gain height, unlike previous mechanisms which are quasi- static. One benefit of dynamics is that it allows climbing with only a single actuated degree of freedom. We show with analysis, simulations and experiments that this dynamic robot is capable of climbing vertically between parallel walls. We introduce simplifications that enable us to obtain closed form approximations of the robot motion. Furthermore, this provides us with some design considerations and insights into the mechanism's ability to climb.

We have developed a novel highly articulated robotic probe (HARP) that can thread through tightly packed volumes without disturbing the surrounding tissues and organs. We use cardiac surgery as the focal application of this work. As such, we have designed the HARP to enter the pericardial cavity through a subxiphoid port. The surgeon can effectively reach remote intrapericardial locations on the epicardium and deliver therapeutic interventions under direct control. Our device differs from others in that we use conventional actuation and still have great maneuverability. We have performed proof-of-concept clinical experiments to give us preliminary validation of the ideas presented here.

This paper introduces a new approach to identify singularities of planar parallel manipulators (PPMs). This method is based on Maxwell's reciprocal figure theory which establishes a duality between self stressed frameworks and reciprocal figures, which are abstract dual representations of frameworks. We use line geometry tools to introduce a new graphical construction called the mechanism's line of action graph (MLG). The MLG is introduced in order to implement Maxwell's reciprocal figure theory to mechanisms. We show that the configurations where the MLG has a connected reciprocal figure imply a singularity in the mechanism. This singularity analysis tool is also used to trace the singularity loci of the PPM. Finally, we provide detailed examples of the singularity analysis of two common PPMs; one consists of three limbs with a passive revolute joint, actuated prismatic joint and another passive revolute joint (3-RPR), the other consists of three limbs with three revolute joints, where only the first is actuated (3-RRR)

We address the problem of knee pathology assessment by using screw theory to describe the knee motion and by using the screw representation of the motion as an input to a machine learning classifier. The flexions of knees with different pathologies are tracked using an optical tracking system. The screw parameters which describe the transformation of the tibia with respect to the femur in each two successive observation are represented as the instantaneous screw axis of the motion given in its Plucker line coordinate, along with its corresponding pitch. The set of screw parameters associated with a particular knee with a given pathology is then identified and clustered in R6to form a "signature" of the motion for the given pathology. Bone model and two cadaver knees with different pathologies were tracked, and the resulting screws were used to train a classifier system. The system was then tested successfully with new, never trained before data. The classifier demonstrated a very high success rate in identifying the knee pathology