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

by   Sam Harper, et al.

Multi-robot systems face challenges in reducing human interventions as they are often deployed in dangerous environments. It is therefore necessary to include a methodology to assess robot failure rates to reduce the requirement for costly human intervention. A solution to this problem includes robots with the ability to work together to ensure mission resilience. To prevent this intervention, robots should be able to work together to ensure mission resilience. 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 multi-robot fleet. This digital twin considers mission resilience, decision making and a run-time reliability ontology for failure detection to enable the resilience of a multi-robot fleet. This creates the cooperation, corroboration, and collaboration of diverse robots to leverage the capability of robots and support recovery of a failed robot.



page 2

page 3

page 4

page 5


Symbiotic System Design for Safe and Resilient Autonomous Robotics in Offshore Wind Farms

To reduce Operation and Maintenance (O M) costs on offshore wind farms...

Bio-inspired Multi-robot Autonomy

Increasingly, high value industrial markets are driving trends for impro...

Real-Time Visual Localisation in a Tagged Environment

In a robotised warehouse a major issue is the safety of human operators ...

Intervention scenarios to enhance knowledge transfer in a network of firm

We investigate a multi-agent model of firms in an R&D network. Each firm...

Resilience and Energy-Awareness in Constraint-Driven-Controlled Multi-Robot Systems

In the context of constraint-driven control of multi-robot systems, in t...

Multi-Robot Collaborative Perception with Graph Neural Networks

Multi-robot systems such as swarms of aerial robots are naturally suited...

Learning the Noise of Failure: Intelligent System Tests for Robots

Roboticists usually test new control software in simulation environments...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.