Electrical Engineering
      and Computer Sciences

Electrical Engineering and Computer Sciences

COLLEGE OF ENGINEERING

UC Berkeley

   

2010 Research Summary

The Stanford/Berkeley Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC)

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Haomiao Huang, Michael Vitus, Jeremy Gillula, Patrick Bouffard, Eugene Li, Tony Mercer, Christopher Berner and Claire Tomlin

The Stanford/Berkeley Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC) is a multi-vehicle testbed used to demonstrate new concepts in multi-agent control on a real-world platform. STARMAC consists of six quadrotor vehicles that are equipped with sufficient sensing and computing power to enable completely autonomous operation, from low level tasks (e.g. waypoint and trajectory following) to high-level optimal control strategies (e.g. information theoretic cooperative search and rescue). In order to make such a testbed easy to use, we focused on a small, light, low cost design, which presented numerous opportunities for innovative work.[1]

The resulting vehicles can fly safely in both indoor and outdoor environments, can carry a wide variety of payloads (including laser range-finders and PC104 computers) and have simple, reconfigurable construction with low maintenance requirements.[2]

Previous work on STARMAC has covered a wide variety of topics, including cooperative search and rescue[3], information theoretic control[4], cooperative collision avoidance[5], optimal path planning[6], and designing guaranteed safe acrobatic trajectories[7]. Current work is focused on integrating perception capabilities onto STARMAC, to enable the vehicles to understand, respond to, and reason about their environment.

Figure 1
Figure 1: One of the STARMAC vehicles in flight.

[1]
Gabriel Hoffmann, Dev Gorur Rajnarayan, Steven L. Waslander, David Dostal, Jung Soon Jang, and Claire J. Tomlin. The Stanford Testbed of Autonomous Rotorcraft for Multi-Agent Control. In the Digital Avionics System Conference 2004, Salt Lake City, UT, November 2004.
[2]
Gabriel M. Hoffmann, Haomiao Huang, Steven L. Waslander, and Claire J. Tomlin. Quadrotor helicopter flight dynamics and control: Theory and experiment. In Proceedings of the AIAA Guidance, Navigation, and Control Conference, Hilton Head, SC, August 2007. AIAA Paper Number 2007-6461.
[3]
G. M. Hoffmann, S. L. Waslander, and C. J. Tomlin, Mutual Information Methods with Particle Filters for Mobile Sensor Network Control, Proceedings of the 45th IEEE Conference on Decision and Control, San Diego, December 2006.
[4]
G. M. Hoffmann, S. L. Waslander, and C. J. Tomlin, Distributed cooperative search using information-theoretic costs for particle filters with quadrotor applications, Proceedings of the AIAA Guidance, Navigation, and Control Conference, Keystone, AIAA Paper 2006-6576, August 2006.
[5]
Steven L. Waslander and Claire J. Tomlin. Decentralized collision avoidance for autonomous aerial vehicles via nash bargaining. in preparation for AIAA Journal of Guidance, Control and Dynamics, 2009.
[6]
Michael Vitus, Vijay Pradeep, Gabriel M. Hoffmann, Steven L. Waslander, and Claire J. Tomlin. Tunnel-MILP: Path planning with sequential convex polytopes In 2008 AIAA Guidance, Navigation and Control Conference and Exhibit, Honolulu, Hawaii, USA, August 2008.
[7]
Jeremy Gillula, Haomiao Huang, Michael P. Vitus and Claire J. Tomlin. Design and Analysis of Hybrid Systems With Applications to Robotic Aerial Vehicles. In the Proceedings of the 14th International Symposium of Robotics Research, Lucerne, Switzerland, September, 2009.