Trajectory Optimization for a Collaborative Robot UR5 in a Scenario with Obstacles

Abstract

Collaborative robots are becoming more present in various activities, inside and outside the industry. The use of these robots allows greater precision and accuracy in carrying out the tasks. However, it is important to take into account some factors to ensure the safety of the system, such as the ability to avoid obstacles that may be present in the operating environment. In this work, we propose a system for trajectory optimization of a robotic manipulator in complex environments using the algorithms Covariant Hamiltonian Optimization for Motion Planning (CHOMP) and Stochastic Trajectory Optimization for Motion Planning (STOMP), and an RGB+D sensor for obstacle detection. The entire system was implemented based on the open-source framework Robot Operating System (ROS). Performance of the algorithms was analyzed based on their success rate, planning time, and duration of the generated trajectory. Results indicate that the proposed system can generate feasible and collision-free trajectories in static environments.