Continuous-Time Trajectory Optimization for Decentralized Multi-Robot Navigation. (2020)

• Record Type: Journal Article
• Authors: Krishnan, Shravan; Rajagopalan, Govind Aadithya; Kandhasamy, Sivanathan; Shanmugavel, Madhavan
• Is Part Of: IFAC-PapersOnLine. Volume 53(2020)Supplement
• Page Start: 494
• Page End: 499
• Publication Date: 2020
• Subjects: Trajectory Planning -- Optimal Control -- Multi-Robot Systems; Automatic control -- Periodicals; 629.805
• DOI: 10.1016/j.ifacol.2020.06.083
• Languages: English
• ISSNs: 2405-8963

Abstract

Abstract: Multi-robot systems have begun to permeate into a variety of different fields, but collision-free navigation in a decentralized manner is still an arduous task. Typically, the navigation of high speed multi-robot systems demands replanning of trajectories to avoid collisions with one another. This paper presents an online replanning algorithm for trajectory optimization in labeled multi-robot scenarios. With reliable communication of states among robots, each robot predicts a smooth continuous-time trajectory for every other remaining robots. Based on the knowledge of these predicted trajectories, each robot then plans a collision-free trajectory for itself. The collision-free trajectory optimization problem is cast as a non linear program (NLP) by exploiting polynomial based trajectory generation. The algorithm was tested in simulations on Gazebo with aerial robots.