Real-time pursuit-evasion with humanoid robots

We consider a pursuit-evasion problem between humanoids. In our scenario, the pursuer enters the safety area of the evader headed for collision, while the latter executes a fast evasive motion. Control schemes are designed for both the pursuer and the evader. They are structurally identical, although the objectives are different: the pursuer tries to align its direction of motion with the line-of-sight to the evader, whereas the evader tries to move in a direction orthogonal to the line-of-sight to the pursuer. At the core of the control scheme is a maneuver planning module which makes use of closed- form expressions exclusively. This allows its use in a replanning framework, where each robot updates its motion plan upon completion of a step to account for the perceived motion of the other. Simulation and experimental results on NAO humanoids reveal an interesting asymptotic behavior which was predicted using unicycle as template models for trajectory generation

Autonomous Behaviors With A Legged Robot

Over the last ten years, technological advancements in sensory, motor, and computational capabilities have made it a real possibility for a legged robotic platform to traverse a diverse set of terrains and execute a variety of tasks on its own, with little to no outside intervention. However, there are still several technical challenges to be addressed in order to reach complete autonomy, where such a platform operates as an independent entity that communicates and cooperates with other intelligent systems, including humans. A central limitation for reaching this ultimate goal is modeling the world in which the robot is operating, the tasks it needs to execute, the sensors it is equipped with, and its level of mobility, all in a unified setting. This thesis presents a simple approach resulting in control strategies that are backed by a suite of formal correctness guarantees. We showcase the virtues of this approach via implementation of two behaviors on a legged mobile platform, autonomous natural terrain ascent and indoor multi-flight stairwell ascent, where we report on an extensive set of experiments demonstrating their empirical success. Lastly, we explore how to deal with violations to these models, specifically the robot\u27s environment, where we present two possible extensions with potential performance improvements under such conditions

Examples of Gibsonian Affordances in Legged Robotics Research Using an Empirical, Generative Framework

Evidence from empirical literature suggests that explainable complex behaviors can be built from structured compositions of explainable component behaviors with known properties. Such component behaviors can be built to directly perceive and exploit affordances. Using six examples of recent research in legged robot locomotion, we suggest that robots can be programmed to effectively exploit affordances without developing explicit internal models of them. We use a generative framework to discuss the examples, because it helps us to separate—and thus clarify the relationship between—description of affordance exploitation from description of the internal representations used by the robot in that exploitation. Under this framework, details of the architecture and environment are related to the emergent behavior of the system via a generative explanation. For example, the specific method of information processing a robot uses might be related to the affordance the robot is designed to exploit via a formal analysis of its control policy. By considering the mutuality of the agent-environment system during robot behavior design, roboticists can thus develop robust architectures which implicitly exploit affordances. The manner of this exploitation is made explicit by a well constructed generative explanation

Distributed, adaptive deployment for nonholonomic mobile sensor networks : theory and experiments

In this work we show the Lyapunov stability and convergence of an adaptive and decentralized coverage control for a team of mobile sensors. This new approach assumes nonholonomic sensors rather than the usual holonomic sensors found in the literature. The kinematics of the unicycle model and a nonlinear control law in polar coordinates are used in order to prove the stability of the controller applied over a team of mobile sensors. This controller is adaptive, which means that the mobile sensors are able to estimate and map a density function in the sampling space without a previous knowledge of the environment. The controller is decentralized, which means that each mobile sensor has its own estimate and computes its own control input based on local information. In order to guarantee the estimate convergence, the mobile sensors implement a consensus protocol in continuous time assuming a fixed network topology and zero communication delays. The convergence and feasibility of the coverage control algorithm are verified through simulations in Matlab and Stage. The Matlab simulations consider only the kinematics of the mobile sensors and the Stage simulations consider the dynamics and the kinematics of the sensors. The Matlab simulations show successful results since the sensor network carries out the coverage task and distributes itself over the estimated density function. The adaptive law which is defined by a differential equation must be approximated by a difference equation to be implementable in Stage. The Stage simulations show positive results, however, the system is not able to achieve an accurate estimation of the density function. In spite of that, the sensors carry out the coverage task distributing themselves over the sampling space. Furthermore, some experiments are carried out using a team of four Pioneer 3-AT robots sensing a piecewise constant light distribution function. The experimental results are satisfactory since the robots carry out the coverage task. However, the accuracy of the estimation is affected by the approximation of the adaptation law by difference equations, the number of robots and sensor sensitivity. Based on the results of this research, the decentralized adaptive coverage control for nonholonomic vehicles has been analyzed from a theoretical approach and validated through simulation and experimentation with positive results. As a future work we will investigate: (i) new techniques to improve the implementation of the adaptive law in real time,(ii) the consideration of the dynamics of the mobile sensors, and (iii) the stability and convergence of the adaptive law for continuous-time variant density function

Formation control of nonholonomic mobile robots: the virtual structure approach

PhDIn recent years, there has been a considerable growth in applications of multi-robot systems as opposed to single-robot systems. This thesis presents our proposed solutions to a formation control problem in which mobile robots are required to create a desired formation shape and track a desired trajectory as a whole. In the first instance, we study the formation control problem for unicycle mobile robots. We propose two control algorithms based on a cascaded approach: one based on a kinematic model of a robot and the other based on a dynamic model. We also propose a saturated controller in which actuator limitations are explicitly accounted for. To demonstrate how the control algorithms work, we present an extensive simulation and experimental study. Thereafter we move on to formation control algorithms in which the coordination error is explicitly defined. Thus, we are able to give conditions for robots keeping their desired formation shape without necessarily tracking the desired trajectory. We also introduce a controller in which both trajectory tracking and formation shape maintenance are achieved as well as a saturated algorithm. We validate the applicability of the introduced controllers in simulations and experiments. Lastly, we study the formation control problem for car-like robots. In this case we develop a controller using the backstepping technique. We give conditions for robots keeping their desired formation shape while failing to track their desired trajectories and present simulation results to demonstrate the applicability of the proposed controlle

Active Sensing for Dynamic, Non-holonomic, Robust Visual Servoing

We consider the problem of visually servoing a legged vehicle with unicycle-like nonholonomic constraints subject to second-order fore-aft dynamics in its horizontal plane. We target applications to rugged environments characterized by complex terrain likely to perturb significantly the robot’s nominal dynamics. At the same time, it is crucial that the camera avoid “obstacle” poses where absolute localization would be compromised by even partial loss of landmark visibility. Hence, we seek a controller whose robustness against disturbances and obstacle avoidance capabilities can be assured by a strict global Lyapunov function. Since the nonholonomic constraints preclude smooth point stabilizability we introduce an extra degree of sensory freedom, affixing the camera to an actuated panning axis mounted on the robot’s back. Smooth stabilizability to the robot-orientation-indifferent goal cycle no longer precluded, we construct a controller and strict global Lyapunov function with the desired properties. We implement several versions of the scheme on a RHex robot maneuvering over slippery ground and document its successful empirical performance. For more information: Kod*La