The Stanford/Berkeley Testbed of Autonomous Rotorcraft for Multi-Agent Control (STARMAC)
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.
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.
Previous work on STARMAC has covered a wide variety of topics, including cooperative search and rescue, information theoretic control, cooperative collision avoidance, optimal path planning, and designing guaranteed safe acrobatic trajectories. 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: One of the STARMAC vehicles in flight.
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