Resource-Aware Estimation and Control for Edge Robotics: A Set-Based Approach

The evolution of the Industrial Internet of Things (IIoT) and edge computing enables resource-constrained mobile robots to offload the computationally intensive localization algorithms. Naturally, utilizing the remote resources of an edge server to offload these tasks encounters the challenge of a joint co-design in communication, control, estimation, and computing infrastructure. We introduce a set-based estimation offloading framework, for the specific case of the navigation of a unicycle robot toward a target position. The robot is subject to modeling and measurement uncertainties, and the estimation set is calculated using overapproximation techniques that alleviate additional computations. A switching set-based control mechanism provides accurate navigation and triggers more precise estimation algorithms when needed. To guarantee the convergence of the system and optimize the utilization of remote resources, a utility-based offloading mechanism is designed, which takes into account both the dynamic network conditions and the available computing resources at the network edge. The performance of the proposed framework is demonstrated through simulations and comparison with alternative offloading schemes.

Automated summary

The evolution of IIoT and edge computing allows resource-constrained mobile robots to offload computationally intensive localization algorithms. This poses a challenge in joint co-design of communication, control, estimation, and computing infrastructure when utilizing remote resources. A set-based estimation offloading framework is introduced for unicycle robot navigation, accounting for modeling and measurement uncertainties. A switching set-based control mechanism and utility-based offloading mechanism are designed to ensure accurate navigation and optimize resource utilization.