A Decentralized Multi-Agent Unmanned Aerial System to Search, Pick Up, and Relocate Objects
This addresses search and rescue robotics by integrating multi-agent exploration, object handling, and gripping into a working system, though it is incremental as it combines simple existing components.
The authors tackled the problem of integrating multiple autonomous aerial robots to search for, pick up, and relocate moving and static objects with unknown locations, achieving reliable performance and placing second out of 17 in a robotics challenge.
We present a fully integrated autonomous multi- robot aerial system for finding and collecting moving and static objects with unknown locations. This task addresses multiple relevant problems in search and rescue (SAR) robotics such as multi-agent aerial exploration, object detection and tracking, and aerial gripping. Usually, the community tackles these problems individually but the integration into a working system generates extra complexity which is rarely addressed. We show that this task can be solved reliably using only simple components. Our decentralized system uses accurate global state estimation, reactive collision avoidance, and sweep planning for multi-agent exploration. Objects are detected, tracked, and picked up using blob detection, inverse 3D-projection, Kalman filtering, visual-servoing, and a magnetic gripper. We evaluate the individual components of our system on the real platform. The full system has been deployed successfully in various public demonstrations, field tests, and the Mohamed Bin Zayed International Robotics Challenge 2017 (MBZIRC). Among the contestants we showed reliable performances and reached second place out of 17 in the individual challenge.