Abstract
SUMMARYThis paper formulates a new scalable algorithm for motion planning and control of multiple point-mass robots. These autonomous robots are designated to move safely to their goals ina prioriknown workspace cluttered with fixed and moving obstacles of arbitrary positions and sizes. The control laws proposed for obstacle and collision avoidance and target convergence ensure that the equilibrium point of the given system is asymptotically stable. Computer simulations with the proposed technique and applications to a team of two planar (RP) manipulators working together in a common workspace are presented. Also, the robustness of the system in the presence of noise is verified through simulations.
Highlights
Active and continuous research in the area of motion planning and control (MPC) of robots has incessantly spanned over the past two decades
The dynamic obstacles may be the mobile robots themselves as well as other solid bodies moving in the workspace
Over the past two decades, researchers have devised numerous algorithms to address motion planning problem for multiple robots taking into account both collision and obstacle avoidances
Summary
Active and continuous research in the area of motion planning and control (MPC) of robots has incessantly spanned over the past two decades. We will control the motion of multiple point-masses in the presence of fixed and moving obstacles in a priori known workspace. A scalable algorithm for obstacle and collision avoidances, and target convergence is proposed that works for multiple point-mass robots with multiple moving and fixed obstacles of arbitrary shapes and sizes. Let Pi be the ith point-mass robot in the z1z2 plane, positioned at (xi, yi) with a circular protective region of radius rPi ≥ 0 and moving with a velocity of vi at time t ≥ 0. Claim 1 With the form of the velocities given by equation [4], the point-mass robot Pi is guaranteed to converge at its target position. The controllers derived will be continuous everywhere along the trajectory of the system It ensures that the turning is initiated when a robot enters the sensing zone.
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