Abstract
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) |
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| Title of host publication | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 6599-6604 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781728162126 |
| DOIs | |
| 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 |
Publication series
| Name | IEEE International Conference on Intelligent Robots and Systems |
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| ISSN (Print) | 2153-0858 |
| ISSN (Electronic) | 2153-0866 |
Conference
| Conference | 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020 |
|---|---|
| Country/Territory | United States |
| City | Las Vegas |
| Period | 10/24/20 → 1/24/21 |
Bibliographical note
Funding Information:*This work was supported by Honeywell Aerospace and MnDRIVE.
Publisher Copyright:
© 2020 IEEE.