Camillo J. Taylor, GRASP Lab, University of Pennsylvania - [home]

Vision-Based Motion Planning and Exploration Algorithms for Mobile Robots



This paper considers the problem of systematically exploring an unfamiliar environment in search of one or more recognizable targets.
The proposed exploration algorithm is based on a novel representation of environments containing visual landmarks called the boundary place graph. This representation records the set of recognizable objects (landmarks) that are visible from the boundary of each
configuration space obstacle. No metric information about the scene geometry is recorded nor are explicit prescriptions for moving between places stored. The exploration algorithm constructs the boundary place graph incrementally from sensor data. Once the robot has
completely explored an environment, it can use the constructed representation to carry out further navigation tasks. In order to precisely characterize the set of environments in which this algorithm is expected to succeed, we provide a necessary and sufficient condition under which the algorithm is guaranteed to discover all of the landmarks. This algorithm has been implemented on our mobile robot platform RJ, and results from these experiments are presented. Importantly, this research demonstrates that it is possible to design and implement provably correct exploration and navigation algorithms that do not require global positioning systems or metric representations of the environment.

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