Department of Mechatronics and Machine Dynamics, Technical University of Cluj-Napoca, 400114 Cluj-Napoca, Romania.
Sensors (Basel). 2022 Jan 4;22(1):373. doi: 10.3390/s22010373.
The paper proposes a novel approach for shape sensing of hyper-redundant robots based on an AHRS IMU sensor network embedded into the structure of the robot. The proposed approach uses the data from the sensor network to directly calculate the kinematic parameters of the robot in modules operational space reducing thus the computational time and facilitating implementation of advanced real-time feedback system for shape sensing. In the paper the method is applied for shape sensing and pose estimation of an articulated joint-based hyper-redundant robot with identical 2-DoF modules serially connected. Using a testing method based on HIL techniques the authors validate the computed kinematic model and the computed shape of the robot prototype. A second testing method is used to validate the end effector pose using an external sensory system. The experimental results obtained demonstrate the feasibility of using this type of sensor network and the effectiveness of the proposed shape sensing approach for hyper-redundant robots.
本文提出了一种基于 AHRS IMU 传感器网络的新型超冗余机器人形状感知方法，该传感器网络嵌入到机器人的结构中。所提出的方法使用传感器网络中的数据直接计算机器人在模块操作空间中的运动学参数，从而减少了计算时间，并为形状感知实现先进的实时反馈系统提供了便利。本文将该方法应用于基于铰接关节的超冗余机器人的形状感知和姿态估计，该机器人的 2-DoF 模块串联连接。使用基于硬件在环技术的测试方法，作者验证了计算得到的运动学模型和机器人原型的计算形状。使用外部传感器系统的第二种测试方法用于验证末端执行器的姿态。所获得的实验结果证明了使用这种类型的传感器网络的可行性以及针对超冗余机器人的形状感知方法的有效性。
