Optimal Latency Compensator for Improved Performance of Teleoperated UGVs on Soft Terrains

Abstract

Bilateral teleoperation of low-speed Unmanned Ground Vehicles (UGVs) on soft terrains is crucial for applications such as space exploration. However, latency arising from transmission delays within the teleoperation system can hinder UGV maneuvering and performance. This paper investigates the impact of latency on the bilateral teleoperation of low-speed UGVs operating on soft terrains and proposes an optimal latency compensator to mitigate this impact for Lunar exploration. Specifically, we propose a genetic algorithm-based predictor framework to optimize the regularization parameters of a model-free predictor. This approach aims to enhance prediction accuracy, thereby improving the performance of the UGV in the presence of latency. Our study revealed a latency threshold of 0.72 seconds is critical for maintaining a stable UGV operation. Furthermore, the proposed predictor framework demonstrates the ability to compensate for the latency by at least 86% Mean Delay Compensation Percentage (MDCP), in contrast to the existing predictor which achieved around 51% for larger delay in the closed-loop teleoperated system. Finally, the developed predictor framework was experimentally validated to compensate for the delays in the teleoperated UGV designed for lunar exploration. The obtained results prove the proposed predictor is effective in compensating for the delays within a closed-loop teleoperated UGV. This effectiveness is showcased through improved performance and transparency.