Using Particle Filters to Find Free Obstacle Trajectories for a Kinematic Chain

Abstract

Abstract:The problem of finding an appropriate path for a mechanical arm that tries to reach a target among obstacles is one of the most important in fields of automation and robotics. It is both a classic inverse kinematics and collision detection problem. This project aimed to construct a tool to plan a path for an articulated arm through a two-dimensional environment with obstacles. The inverse kinematics problem is addressed by heuristics Bayesian particles filter, and the collision detection problem is solved using computational geometry methods for calculating the free configurations space. The proposed tool has a graphical interface with which you can get information from the designed experiments. The feasibility of this approach and its advantages in complex two-dimensional environments is shown. We proved that good results can be obtained with an appropriate selection of the parameters.

Unmanned Combat Aerial Vehicle Path Planning by Brain Storm Optimization Algorithm

“…An algorithm for finding a good path for mechanical arm was proposed in [16]. Bayesian particles filter was used for inverse kinematics problem, while computational geometry was proposed for collision detection problem.…”