Cloudroid Swarm: A QoS‐Aware Framework for Multirobot Cooperation Offloading

Abstract

Computation offloading has been widely recognized as an effective way to promote the capabilities of resource-constrained mobile devices. Recent years have seen a renewal of the importance of this technology in the emerging field of mobile robots, supporting resource-intensive robot applications. However, cooperating to solve complex tasks in the physical world, which is a significant feature of a robot swarm compared to traditional mobile computing devices, has not received in-depth attention in research concerned with traditional computation offloading. In this study, we propose an approach named cooperation offloading, which offloads the intensive communication among robots as well as the computation for compute-intensive and data-intensive tasks. We analyze the performance gain of cooperation offloading by formalizing multirobot cooperative models; in addition, we study offloading decisions. Based on this approach, we design a cloud robotic framework named Cloudroid Swarm and develop several QoS-aware mechanisms to provide a general solution to cooperation offloading with QoS assurance in multirobot cooperative scenes. We implement Cloudroid Swarm to transparently migrate multirobot applications to cloud servers without any code modification. We evaluate our framework using three different multirobot cooperative applications. Our results show that Cloudroid Swarm can be applied to various robotic applications and real-world environments and bring significant benefits in terms of both network optimization and task performance. Besides, our framework has good scalability and can do support as many as 256 robot entities simultaneously.

Prescribed performance adaptive event-triggered consensus control for multiagent systems with input saturation

“…With the rapid development of science and technology, multiagent systems are widely used in many fields, such as multirobot cooperation (Huang et al, 2018 ; Dai et al, 2021 ; Zhai et al, 2021 ), unmanned surface vehicles (Zhou et al, 2020 ; Gu et al, 2021 ; Huang et al, 2021 ), unmanned aerial vehicles (Gong et al, 2021 ; Tran et al, 2021 ; Zhou and Chen, 2021 ), and other fields. The multiagent system cooperative control mainly includes consensus, formation, and swarm, and the problem of consensus control, as the foundation of multiagent systems cooperative control, has received much attention from scholars (Cai et al, 2021 ; Ning et al, 2021 ; Su H. et al, 2021 ; Wang C. et al, 2021 ; Wei and Xiao, 2021 ).…”