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Locomotion and Reconfiguration Autonomy for Spherical Freeform Modular Robots

Authors: Yuxiao Tu, Guanqi Liang, Di Wu, Xinzhuo Li, Tin Lun Lam Corresponding author: Tin Lun Lam (Email: tllam@cuhk.edu.cn; Website: https://freeformrobotics.org/tllam ) Published in: International Journal of Robotics Research (Accepted) Paper: (To be available) Freeform Robotics: https://freeformrobotics.org Title: Locomotion and Self-reconfiguration Autonomy for Spherical Freeform Modular Robots Abstract: Modular robotic systems consist of multiple repeated modules capable of transforming into various configurations. Matching these configurations to a library enables efficient automation, even with high degrees of freedom and strict motion constraints. Prior work has automated cube-based modular robots by mapping predefined gait sequences to module controllers. However, due to limited control accuracy and docking misalignment tolerance, such methods struggle with robust 3D self-reconfiguration without external sensors. Freeform modular robots, featuring continuous spherical joint connections and no fixed-point connectors, offer greater misalignment tolerance and environmental adaptability. Yet, their redundant degrees of freedom and incompatible reconfiguration approaches make existing library-based systems unsuitable. This article proposes a novel autonomy framework for locomotion and self-reconfiguration of spherical freeform modular robots. Module connections are modeled as either spherical joints or parallel robots using a unified skeletal kinematics approach. Target configurations are achieved via iterative inverse kinematics and command translation. A library with interfaces for design tools defines behaviors and feasible kinematic transitions. Executable behaviors are efficiently retrieved using a configuration matching and mapping algorithm. The system is validated on the FreeSN platform with up to 18 modules and 48 joint motors, laying the groundwork for advanced planning and control in freeform modular robotics.

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文本转语音https://fish.audio/zh-CN/text-to-speech/?modelId=c5c17c9709384ba9a4b294662a2af0b1&taskId=92aaab3d342a4fa383c522edced9012e 语音转语音https://www.weights.gg/ 仅供学习

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AI时代的革新系列（五）中国流的消失详解 理解后大局观提升

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施一公：Ai对生物学的影响