Dynamic collision avoidance for multiple robotic manipulators based on a non-cooperative multi-agent game

Abstract

A flexible operation of multiple robotic manipulators in a shared workspace requires an online trajectory planning with static and dynamic collision avoidance. In this work, we propose a real-time capable motion control algorithm, based on non-linear model predictive control, which accounts for static and dynamic collision avoidance. The proposed algorithm is formulated as a non-cooperative game, where each robot is considered as an agent. Each agent optimizes its own motion and accounts for the predicted movement of surrounding agents. We propose a novel approach to formulate the dynamic collision constraints. Additionally, we account for deadlocks that might occur in a setup of multiple robotic manipulators. We validate our algorithm on a pick and place scenario for four collaborative robots operating in a common workspace in the simulation environment Gazebo. The robots are controlled by the Robot Operating System (ROS). We demonstrate, that our approach is real-time capable and, due to the distributed nature of the approach, easily scales to an arbitrary number of robot manipulators in a shared workspace.

Figures (16)

• Figure 1: Setup for a pick and place scenario with four collaborative UR$3$ manipulators.
• Figure 2: Control structure of collision free online motion control for multiple robotic manipulators.
• Figure 3: Illustrative approximation of robots' geometry with ellipsoids and line segments from the perspective of the robot $R_i(\cdot)$ on the right side.
• Figure 4: A comparison between the projection operator $P(\alpha)$ and the approximated function $\hat{P}(\alpha)$ with parameter $c=20$.
• Figure 5: Simulation setup with $2$ modules of UR$3$ robots.