We investigate a multi-agent planning problem, where each agent aims to achieve an individual task while avoiding collisions with others. We assume that each agent's task is expressed as a Time-Window Temporal Logic (TWTL) specification defined over a 3D environment. We propose a decentralized receding horizon algorithm for online planning of trajectories. We show that when the environment is sufficiently connected, the resulting agent trajectories are always safe (collision-free) and lead to the satisfaction of the TWTL specifications or their finite temporal relaxations. Accordingly, deadlocks are always avoided and each agent is guaranteed to safely achieve its task with a finite time-delay in the worst case. Performance of the proposed algorithm is demonstrated via numerical simulations and experiments with quadrotors.
|Original language||English (US)|
|Title of host publication||2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Oct 24 2020|
|Event||2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 - Las Vegas, United States|
Duration: Oct 24 2020 → Jan 24 2021
|Name||IEEE International Conference on Intelligent Robots and Systems|
|Conference||2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020|
|Period||10/24/20 → 1/24/21|
Bibliographical noteFunding Information:
*This work was supported by Honeywell Aerospace and MnDRIVE.
© 2020 IEEE.