[Robot Perception and Learning] Lab Meeting March 31st, 2008 (Hero)

Design and evaluation of a reactive and deliberative collision avoidance and escape architecture for autonomous robots

Abstract
We present the design and evaluation of an architecture for collision avoidance and escape of mobile autonomous robots operating in unstructured environments. The approach mixes both reactive and deliberative components. This provides the vehicle’s behavior designers with an explicit means to design-in avoidance strategies that match system requirements in concepts of operations and for robot certification. The now traditional three layer architecture is extended to include a fourth Scenario layer, where scripts describing specific responses are selected and parameterized on the fly. A local map is maintained using available sensor data, and adjacent objects are combined as they are observed. This has been observed to create safer trajectories. Objects have persistence and fade if not re-observed over time. In common with behavior based approaches, a reactive layer is maintained containing pre-defined knee jerk responses for extreme situations. The reactive layer can inhibit outputs from above. Path planning of updated goal point outputs from the Scenario layer is performed using a fast marching method made more efficient through lifelong planning techniques. The architecture is applied to applications with Autonomous Underwater Vehicles. Both simulated and open water tests are carried out to establish the performance and usefulness of the approach.

http://www.springerlink.com/content/87704333473236x3/