Bio-inspired sensorimotor control systems may be appealing to roboticists who try to solve problems of multiDOF humanoids and human-robot interactions. This paper presents a simple posture control concept from neuroscience, called disturbance estimation and compensation, DEC concept [1]. It provides human-like mechanical compliance due to low loop gain, tolerance of time delays, and automatic adjustment to changes in external disturbance scenarios. Its outstanding feature is that it uses feedback of multisensory disturbance estimates rather than 'raw' sensory signals for disturbance compensation. After proof-of-principle tests in 1 and 2 DOF posture control robots, we present here a generalized DEC control module for multi-DOF robots. In the control layout, one DEC module controls one DOF (modular control architecture). Modules of neighboring joints are synergistically interconnected using vestibular information in combination with joint angle and torque signals. These sensory interconnections allow each module to control the kinematics of the more distal links as if they were a single link. This modular design makes the complexity of the robot control scale linearly with the DOFs and error robustness high compared to monolithic control architectures. The presented concept uses Matlab/Simulink (The MathWorks, Natick, USA) for both, model simulation and robot control and will be available as open library
翻译:生物启发感官模型控制系统可能会吸引那些试图解决多多DOF类人类和人-机器人相互作用问题的机器人学家。本文展示了来自神经科学的简单姿态控制概念,称为扰动估计和补偿,DEC概念[1]。由于循环增益低、耐受时间拖延和自动调整以适应外部扰动情景的变化,它提供了人型机械合规。它的突出特征是,它使用多感知干扰估计的反馈,而不是“原始”感官信号来补偿扰动。在1和2 DOF姿态控制机器人的校正测试之后,我们在这里为多DOF机器人提供了一个通用的DE控制模块。在控制布局中,一个DEC模块控制一个DOF(模式控制结构)。 邻接合的模块具有协同性,使用与联合角度和托尔格信号相结合的背感应信息。这些感应连接使每个模块能够控制更不愉快的连接的动态。这种模块设计使得机器人控制规模的复杂度与IMF的直线级控制模块相比, 将IMF 和IMF IMVA 的错控系统结构作为高。