Problem
Research questions and friction points this paper is trying to address.
Continuum robot
Pose estimation
Configuration estimation
Vision-denied environments
Magnetic based In-situ Self 3D Pose Estimation for a Modular Soft Tendon-Driven Continuum Robot via IMU-Fusion
🤖 AI Summary
This study addresses the challenge of configuration estimation for continuum robots in the absence of external visual feedback by proposing a distributed sensing scheme that integrates inertial measurement units (IMUs) with active magnetic fields. Through a multi-source data fusion algorithm, the proposed method achieves embedded self-perception, enabling precise localization without external cameras while supporting high-frequency state updates at 16.7 Hz. Experimental results demonstrate that the system exhibits excellent real-time performance, effectively maintaining the desired pose of the end-effector and facilitating stable closed-loop control. This work establishes a novel paradigm for vision-free autonomous perception of continuum robots operating within confined spaces.
📝 Abstract
Continuum robots are well suited for gentle manipulation because of their inherent compliance and ability to adapt to complex environments. However, their continuously deformable structure makes accurate configuration estimation challenging, particularly when external vision systems are unavailable or obstructed. In this work, we present an embedded pose sensing framework that combines inertial measurement units (IMUs) and active magnetic fields to estimate the robot configuration without relying on external cameras. The angular measurements from the IMU and magnetic-field references are fused to improve local orientation estimation and reduce accumulated orientation error during operation. This pose sensing scheme achieves an update rate of 16.7~Hz, allowing real-time feedback. The proposed system is experimentally validated through closed-loop control, where the estimated robot configuration is used to maintain the end-effector at a desired position while interacting with an object. These results demonstrate the potential of distributed magnetic--inertial sensing for real-time pose estimation and closed-loop control of continuum robots.
Innovation
Methods, ideas, or system contributions that make the work stand out.
Continuum Robot
3D Pose Estimation
IMU-Magnetic Fusion
In-situ Sensing
Closed-loop Control
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