Addressing Non-Intervention Challenges via Resilient Robotics Utilizing a Digital Twin

Abstract

Heterogeneous robot teams face challenges in reducing human interventions due to robot failure and environmental challenges in dangerous unstructured environments. It is therefore necessary to create a methodology to assess robot fleet failure rates to reduce the requirement for costly human intervention. A solution to this problem includes robots with the ability to work together symbiotically to overcome mission resilience challenges. However, robotic platforms generally lack built-in interconnectivity with other platforms from different vendors. This work aims to tackle this issue by enabling the functionality through a bidirectional digital twin. The twin enables the human operator to transmit and receive information to and from the heterogeneous multi-robot fleet. This digital twin considers autonomy for mission resilience and human-led decision making to enable the resilience of a multi-robot fleet. Decision-making within the digital twin triggers the symbiotic digital architecture to preserve mission continuity via adaptive planning in the robotic team. This creates the cooperation, corroboration, and collaboration of diverse robots to leverage the capability via a multi robot fleet, supporting the recovery of a failed robot. This research enables for robots to overcome resilience issues ahead of the requirement for human intervention.