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Modeling Proprioceptive Sensing for Locomotion Control of Hexapod Walking Robot in Robotic Simulator

机译:机器人模拟器中六足步行机器人运动控制的本体感觉建模。

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Proprioceptive sensing encompasses the state of the robot given by its overall posture, forces, and torques acting on its body. It is an important source of information, especially for multi-legged walking robots because it enables efficient locomotion control that adapts to morphological and environmental changes. In this work, we focus on enhancing a simplified model of the multi-legged robot employed in a realistic robotic simulator to provide high-fidelity proprioceptive sensor signals. The proposed model enhancements are based on parameter identification and static and dynamic modeling of the robot. The enhanced model enables the V-REP robotic simulator to be used in real-world deployments of multi-legged robots. The performance of the developed simulation has been verified in the parameter search of dynamic locomotion gait to optimize the locomotion speed according to the limited maximal torques and self-collision free execution.
机译:本体感测包括机器人的状态,该状态由机器人的总体姿态,作用在其身上的力和扭矩确定。它是重要的信息来源,尤其是对于多腿步行机器人而言,因为它可以进行有效的运动控制,以适应形态和环境变化。在这项工作中,我们专注于增强现实机器人模拟器中使用的多腿机器人的简化模型,以提供高保真的本体感受传感器信号。所提出的模型增强功能基于参数识别以及机器人的静态和动态建模。增强的模型使V-REP机器人模拟器可以在多腿机器人的实际部署中使用。在动态运动步态的参数搜索中验证了所开发仿真的性能,以根据有限的最大扭矩和无自碰撞执行来优化运动速度。

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