An Active Cooperative Observation Method for Multi-robots in Three Dimensional Environments

摘要

The solution to multiple mobile robot systems actively and cooperatively observing a moving target (MACO) means the algorithm that tries to pursuit optimal (sub-optimal) observations of the moving target by simultaneously fusing the observational data from multiple robot systems and regulating their behaviors cooperatively. In this paper, the 3D MACO method with two robots is studied. First, at the basis of extended set-membership filter (ESMF), a high precise observation fuse method is presented through combining the information fuse process and the set operations in ESMF algorithm. The new algorithm is as fast as the single ESMF algorithm since it has almost the same computational burden. Second, a coordinate behavior optimization method is given by combining the concept of optimal observational angle and the relative velocity coordinates (RVC) planning method. By using the RVC method, the coordinate behavior optimization can be transferred into a linear planning (LP) problem, which makes its real time application possible. Finally, 3D moving target observational simulations are conducted to verify the feasibility and validity of the proposed algorithm.