New chapter book paper in “Decision Making under Constraints” book edited by M Cerebio and V. Kreinovich
I.-F. Kenmogne, V. Drevelle, E. Marchand. Using Constraint Propagation for Cooperative UAV Localization from Vision and Ranging. In Decision Making under Constraints, Studies in Systems, Decision and Control 276, M Cerebio, V. Kreinovich (eds.), pp. 133-138, Springer Nature, Switzerland, March 2020.
This paper addresses the problem of cooperative localization in a group of unmanned aerial vehicles (UAV) in a bounded error context. The UAVs are equipped with cameras to tracks landmarks, and a communication and ranging system to cooperate with their neighbours. Measurements are represented by intervals, and constraints are expressed on the robots poses (positions and orientations). Each robot first computes a pose domain using only its sensors measurements, by using set inversion via interval analysis (Moore in Interval analysis. Prentice Hall, 1966 [1]). Then, through position boxes exchange, positions are cooperatively refined by constraint propagation in the group. Results are presented with real robot data, and show position accuracy improvement thanks to cooperation.