Real-time moving object recognition and tracking using computation offloading

Mobile robots are widely used for computation-intensive tasks such as surveillance, moving object recognition and tracking. Existing studies perform the computation entirely on robot processors or on dedicated servers. The robot processors are limited by their computation capability; real-time performance may not be achieved. Even though servers can perform tasks faster, the communication time between robots and servers is affected by variations in wireless bandwidths. In this paper, we present a system for realtime moving object recognition and tracking using computation offloading. Offloading migrates computation to servers to reduce the computation time on the robots. However, the migration consumes additional time, referred as communication time in this paper. The communication time is dependent on data size exchanged and the available wireless bandwidth. We estimate the computation and communication needed for the tasks and choose to execute them on robot processors or servers to minimize the total execution time, in order to satisfy real-time constraints.