Task and Joint Space Dual-Arm Compliant Control

2025-04-29

AI Summary

To address poor compliance and low torque control accuracy in high-friction commercial dual-arm robots (e.g., Kinova Gen3) for human–robot collaborative scenarios, this paper proposes a real-time impedance control method. The approach features: (1) a novel smooth interpolation-based compliant control architecture that jointly operates in task and joint spaces; and (2) a model-free friction observer enabling online friction disturbance compensation without precise dynamic modeling. Implemented on ROS2, the system integrates MoveIt! for motion planning and supports high-frequency, closed-loop streaming execution of trajectory commands. Experiments demonstrate sub-centimeter (<1 cm) peg-in-hole accuracy even under strong friction, achieving both high-robustness trajectory tracking and high-fidelity compliant response. The framework enables real-time closed-loop execution of learned, optimized, and teleoperated trajectories.

Technology Category

Intelligent Robots: ManipulationHumans and AI: Human-Aware Planning and Behavior PredictionComputer Vision: Motion & Tracking

Application Category

Responsible Web: Machine-in-the-loop, human agency and autonomyEconomics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAISystems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Robots that interact with humans or perform delicate manipulation tasks must exhibit compliance. However, most commercial manipulators are rigid and suffer from significant friction, limiting end-effector tracking accuracy in torque-controlled modes. To address this, we present a real-time, open-source impedance controller that smoothly interpolates between joint-space and task-space compliance. This hybrid approach ensures safe interaction and precise task execution, such as sub-centimetre pin insertions. We deploy our controller on Frank, a dual-arm platform with two Kinova Gen3 arms, and compensate for modelled friction dynamics using a model-free observer. The system is real-time capable and integrates with standard ROS tools like MoveIt!. It also supports high-frequency trajectory streaming, enabling closed-loop execution of trajectories generated by learning-based methods, optimal control, or teleoperation. Our results demonstrate robust tracking and compliant behaviour even under high-friction conditions. The complete system is available open-source at https://github.com/applied-ai-lab/compliant_controllers.

Problem

• Enhancing compliance in rigid robots for human interaction
• Improving end-effector tracking accuracy in torque control
• Enabling safe interaction and precise task execution

Innovation

• Real-time open-source impedance controller for compliance
• Hybrid joint-space and task-space compliance interpolation
• Model-free observer compensates for friction dynamics