Coordination of Multiple Robotic Vehicles in Obstacle-Cluttered Environments

In this work, we consider the motion control problem for a platoon of unicycle robots operating within an obstacle-cluttered workspace. Each robot is equipped with a proximity sensor that allows it to perceive nearby obstacles as well as a camera to obtain its relative position with respect to its preceding robot. Additionally, no robot other than the leader of the team is able to localize itself within the workspace and no centralized communication network exists, i.e., explicit information exchange between the agents is unavailable. To tackle this problem, we adopt a leader–follower architecture and propose a novel, decentralized control law for each robot-follower, based on the Prescribed Performance Control method, which guarantees collision-free tracking and visual connectivity maintenance by ensuring that each follower maintains its predecessor within its camera field of view while keeping static obstacles out of the line of sight for all time. Finally, we verify the efficacy of the proposed control scheme through extensive simulations.

A Distributed Hunting Approach for Multiple Autonomous Robots

A novel distributed hunting approach for multiple autonomous robots in unstructured mode-free environments, which is based on effective sectors and local sensing, is proposed in this paper. The visual information, encoder and sonar data are integrated in the robot's local frame, and the effective sector is introduced. The hunting task is modelled as three states: search state, round-obstacle state, and hunting state, and the corresponding switching conditions and control strategies are given. A form of cooperation will emerge where the robots interact only locally with each other. The evader, whose motion is a priori unknown to the robots, adopts an escape strategy to avoid being captured. The approach is scalable and may cope with problems of communication and wheel slippage. The effectiveness of the proposed approach is verified through experiments with a team of wheeled robots.

A cell decomposition approach to visibility-based pursuit evasion among obstacles

In this paper, we address the problem of surveillance in an environment with obstacles. We consider the problem in which a mobile observer attempts to maintain visual contact with a target as it moves through an environment containing obstacles. This surveillance problem is a variation of traditional pursuit–evasion games, with the additional condition that the pursuer immediately loses the game if at any time it loses sight of the evader. We analyze this tracking problem as a game of kind. We use the method of explicit policy to compute guaranteed strategies for surveillance for the observer in an environment containing a single corner. These strategies depend on the initial positions of the observer and the target in the workspace. Based on these strategies a partition of the visibility polygon of the players is constructed. The partitions have been constructed for varying speeds of the observer and the target. Using these partitions we provide a sufficient condition for escape of a target in a general environment containing polygonal obstacles. Moreover, for a given initial target position, we provide a polynomial-time algorithm that constructs a convex polygonal region that provides an upper-bound for the set of initial observer positions from which it does not lose the game. We extend our results to the case of arbitrary convex obstacles with differentiable boundaries. We also present a sufficient condition for tracking and provide a lower-bound on the region around the initial position of the target from which the observer can track the target. Finally, we provide an upper bound on the area of the region in which the outcome of the game is unknown.