Real-Time Simulation of Robot Swarms with Restricted Communication Skills

Abstract

The paper presents a new approach and a related software environment for the parallel simulation of swarms of autonomous robots in real time. The software environment has been developed for model based analysis of algorithms to control large swarms of distributed autonomous mobile robots communicating over an unreliable and capacity restricted wireless network. It includes a physical simulation of static obstacles, dynamic obstacles with scriptable movement, soil condition, active jammers, static and dynamic link obstacles with configurable damping as well as noise floors. The simulated ground based mobile robots use control particle belief propagation (C-PBP) as a randomized and sample based model predictive closed loop controller in combination with cost functions to evaluate the situations. We emphasize where the use of shared memory parallelism is beneficial and which inaccuracies in computations are acceptable to increase performance without losing realism.