Real-time Contact State Estimation in Shape Control of Deformable Linear Objects under Small Environmental Constraints

TL;DR

The paper addresses robust real-time shape control of deformable linear objects (DLOs) guided by small environmental fixtures. It introduces two force-derived indicators, the Contact Establishment Indicator (CEI) and the Contact Change Indicator (CCI), to estimate contact state from the interaction between the DLO and fixtures, and integrates them into an adaptive clip-fixing control loop operating at about $1$ kHz. By redesigning manipulation primitives to extend force interaction and leveraging a probabilistic model for contact changes, the approach detects anomalies such as missed contact, blockages, and overforce scenarios, enabling automatic correction within the control framework. Real-world experiments with two robotic arms demonstrate that CEI and CCI improve robustness and success rates across varied clip geometries and fixture offsets, highlighting practical impact for industrial DLO manipulation tasks.

Abstract

Controlling the shape of deformable linear objects using robots and constraints provided by environmental fixtures has diverse industrial applications. In order to establish robust contacts with these fixtures, accurate estimation of the contact state is essential for preventing and rectifying potential anomalies. However, this task is challenging due to the small sizes of fixtures, the requirement for real-time performances, and the infinite degrees of freedom of the deformable linear objects. In this paper, we propose a real-time approach for estimating both contact establishment and subsequent changes by leveraging the dependency between the applied and detected contact force on the deformable linear objects. We seamlessly integrate this method into the robot control loop and achieve an adaptive shape control framework which avoids, detects and corrects anomalies automatically. Real-world experiments validate the robustness and effectiveness of our contact estimation approach across various scenarios, significantly increasing the success rate of shape control processes.

Figures (8)

• Figure 1: Setup. Top: shape control of DLO with 4 environmental fixtures using two robots. Bottom: various clip fixtures.
• Figure 2: Clip fixing and DLO deformation. (a) Top views. From top to bottom: contact-insertion-fixed-overforce movement. (b) Left views. Top: insertion; bottom: fixed.
• Figure 3: Clip fixing process. The red curve represents the DLO. The black fixture represents the clip. The gray polygon represents the robot hand and finger tips. (a), (b), (c) and (d) in the first row describe the ideal clip fixing process. (e), (f), (g) in the second row describe the failures which may happen at different stages. The tendency of displacement (green curve) and contact force (blue curve) are depicted next to each failure. For simplicity, the hand is omitted in the second row.
• Figure 4: Clip dynamics (a) before, (b) during, and (c) after insertion. (d) The change of contact force in this process.
• Figure 5: Top view of cable dynamics in contact with the clip (a) from stretching to contact establishment, and (b) from contact establishment to fixed-in. The clip is represented by the black block in the center. The black arrow on the left describes insertion direction.