Distributed Nonlinear Trajectory Optimization for Multi-Robot Motion Planning

Distributed Nonlinear Trajectory Optimization for Multi-Robot Motion Planning

Ferranti, L. (TU Delft Learning & Autonomous Control)
Lyons, L. (TU Delft Learning & Autonomous Control)
Negenborn, R.R. (TU Delft Transport Engineering and Logistics)
Keviczky, T. (TU Delft Team Tamas Keviczky)
Alonso-Mora, J. (TU Delft Learning & Autonomous Control)

2023

This work presents a method for multi-robot coordination based on a novel distributed nonlinear model predictive control (NMPC) formulation for trajectory optimization and its modified version to mitigate the effects of packet losses and delays in the communication among the robots. Our algorithms consider that each robot is equipped with an onboard computation unit to solve a local control problem and communicate with neighboring autonomous robots via a wireless network. The difference between the two proposed methods is in the way the robots exchange information to coordinate. The information exchange can occur in a following: 1) synchronous or 2) asynchronous fashion. By relying on the theory of the nonconvex alternating direction method of multipliers (ADMM), we show that the proposed solutions converge to a (local) solution of the centralized problem. For both algorithms, the communication exchange preserves the safety of the robots; that is, collisions with neighboring autonomous robots are prevented. The proposed approaches can be applied to various multi-robot scenarios and robot models. In this work, we assess our methods, both in simulation and with experiments, for the coordination of a team of autonomous vehicles in the following: 1) an unsupervised intersection crossing and 2) the platooning scenarios.

Collision avoidance
Delays
fault-tolerant control
multi-robot systems
optimal control
optimization
Packet loss
Planning
Robot kinematics
Robots
Trajectory optimization

http://resolver.tudelft.nl/uuid:c9e067c3-5212-4dbb-ac61-7dabe1f22c7c

https://doi.org/10.1109/TCST.2022.3211130

2023-04-17

1063-6536

IEEE Transactions on Control Systems Technology, 31 (2), 809-824

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 L. Ferranti, L. Lyons, R.R. Negenborn, T. Keviczky, J. Alonso-Mora