Sep 2026· Artificial Life and Robotics· 0 citations· 9 references
Abstract
This paper presents an empirical study of position estimation for the small bioinspired robotic mouse TUCmouse. The objective was to integrate a low-cost inertial measurement unit (IMU) into the robot and evaluate whether approximate indoor position estimation can be achieved without external onboard localization sensors. Although established dead-reckoning and legged-robot state-estimation methods exist, applying them to a small, lightweight robot introduces additional challenges related to scale, sensor noise, body dynamics, and the lack of direct foot-contact sensing. Despite these challenges, this study evaluates three simplified approaches: orientation-aided step counting, foot-kinematic estimation, and an EKF-based method using IMU prediction with covariance-weighted kinematic and zero-velocity pseudomeasurements. Experiments on wooden and elastomeric polymer surfaces show that the EKF-based method achieves the lowest endpoint error among the tested methods. The results demonstrate both the potential and the limitations of low-cost inertial sensing for short-range approximate localization on small bioinspired robots.
Fast and accurate measurement of external disturbances is critical for legged robots in complex environments. While physical force/torque (F/T) sensors provide direct measurements, they are susceptible to high-frequency noise and mechanical damage. To address this challenge, this article proposes a proprioceptive measu...
Jing-Yu Sun, Zi-Xuan Wang, Ya-Jie Gao et al.· IEEE Transactions on Instrum...· 0 citations
Robust proprioceptive state estimation is crucial for legged robots, particularly in challenging environments where exteroceptive sensors are unreliable. While traditional leg odometry typically relies on a single body-mounted inertial measurement unit (IMU) fused with leg kinematics via an extended Kalman filter (EKF)...
Yi-Cheng Zhou, Long-Wen Chen, Qing-Hua Yu et al.· 0 citations
Recent magnetometer-free inertial measurement unit (IMU) methods can reduce drift in joint motion estimation using rigid-body constraints, but they typically require pre-calibrated sensor locations, assumptions of specific joint models (e.g., hinge joints) or limited motion types, or an external reference for global or...
Rui-Yuan Li, Hassan Osman, Ajay Seth et al.· 0 citations
Objective: Data-driven models that estimate physiological states, particularly biological joint moments, are widely used in exoskeleton control. However, these estimators are often coupled to device-specific sensor configurations, limiting controller transfer and the use of open-source biomechanics datasets. Methods: W...
Jinwoo Hwang, I. Park, Changseob Song et al.· 1 citation
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 th...
Zheng Cao, Guo Ning Sue, Xiang-Yun Bu et al.· 0 citations
Flexible robot links challenge the rigid-body assumption, making joint measurements alone insufficient for accurate manipulation. This paper introduces a flexibility-aware manipulation framework that connects structural dynamics directly to sensing, kinematics, and control. Instead of prescribing a dense inertial measu...
A. H. Barjini, S. Yaqubi, P. Mustalahti et al.· 0 citations
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