Cooperative Offloading for Multiple Robot Applications

Computation offloading has been widely recognized as an effective way to promote the capabilities of resource-constrained mobile devices. The past years have seen a renewed importance of this technology in the emerging field of mobile robots. However, a significant feature of robots compared to traditional mobile computing devices (e.g. smartphones) is that they must collaborate to solve complex tasks in the physical world in many cases, which implies intensive data exchange among the robot peers. This characteristic has not been dealt with in-depth in traditional computation offloading research. In this paper, we propose an approach called Cooperative Offloading, which takes into account the cooperation among mobile devices as well as the communication it brings in computation offloading. Firstly, we propose the offloading decision approach that deals with offloading from a set of robots that cooperate to finish a specific task. Secondly, we present a set of mechanisms to optimize the data transfer path on network topology in multi-robot applications, which can significantly reduce the bandwidth consumption of the robot wireless network. Based on the cooperative offloading approach, we realized a cloud robotics framework called Cloudroid Swarm. Evaluations based on real-life applications have shown that Cloudroid Swarm brings more than five times performance promotion compared to the setup without offloading or with individual computation offloading.