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Real-time Digital Double Framework to Predict Collapsible Terrains for Legged Robots

Haddeler, G; Palanivelu, HP; Ng, YC; Colonnier, F; Adiwahono, AH; Li, Z; Chew, CM; (2022) Real-time Digital Double Framework to Predict Collapsible Terrains for Legged Robots. In: IEEE International Conference on Intelligent Robots and Systems. (pp. pp. 10387-10394). IEEE: Kyoto, Japan. Green open access

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Abstract

Inspired by the digital twinning systems, a novel real-time digital double framework is developed to enhance robot perception of the terrain conditions. Based on the very same physical model and motion control, this work exploits the use of such simulated digital double synchronized with a real robot to capture and extract discrepancy information between the two systems, which provides high dimensional cues in multiple physical quantities to represent differences between the modelled and the real world. Soft, non-rigid terrains cause common failures in legged locomotion, whereby visual perception solely is insufficient in estimating such physical properties of terrains. We used digital double to develop the estimation of the collapsibility, which addressed this issue through physical interactions during dynamic walking. The discrepancy in sensory measurements between the real robot and its digital double are used as input of a learning-based algorithm for terrain collapsibility analysis. Although trained only in simulation, the learned model can perform collapsibility estimation successfully in both simulation and real world. Our evaluation of results showed the generalization to different scenarios and the advantages of the digital double to reliably detect nuances in ground conditions.

Type: Proceedings paper
Title: Real-time Digital Double Framework to Predict Collapsible Terrains for Legged Robots
Event: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Dates: 23 Oct 2022 - 27 Oct 2022
ISBN-13: 9781665479271
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/IROS47612.2022.9981613
Publisher version: https://doi.org/10.1109/IROS47612.2022.9981613
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Legged locomotion, Training, Estimation, Robot sensing systems, Real-time systems, Sensors, Synchronization
UCL classification: UCL
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science
URI: https://discovery.ucl.ac.uk/id/eprint/10164223
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