A Novel Online Whole-Body Motion Planning Algorithm for Supervisory Control of a Legged Mobile Manipulator

In this paper, a novel online whole-body motion planning algorithm for supervisory control of a legged mobile manipulator (LMM) is presented. The inputs to the proposed algorithm are the updates to the end-effector’s desired position in Cartesian coordinate system, given continuously at a constant frequency. The algorithm plans the trajectories and calculates the joint space parameters of the LMM in real time and returns all the joint angles continuously, at the same frequency, as the outputs. In the current implementation, the incremental inputs are given to the algorithm using a joystick by the user. To ensure a singularity-free motion of the LMM, the proposed algorithm plans adaptive stroke lengths for the trunk body. The algorithm is designed to be highly modular, so that any necessary improvement to it can be made easily. The proposed algorithm is tested by implementing it on a virtual robot in Gazebo simulation and then, validated on a physical prototype of a hexapod mobile manipulator.

[1]  Dilip Kumar Pratihar,et al.  Study on feet forces' distributions, energy consumption and dynamic stability measure of hexapod robot during crab walking , 2019, Applied Mathematical Modelling.

[2]  Dilip Kumar Pratihar,et al.  Coordinated Motion Planning of Legged Mobile Manipulator for Tracking the Given End-Effector’s Trajectory , 2019 .

[3]  H. Hahn.  Rigid body dynamics of mechanisms , 2002 .

[4]  Rong Xiong,et al.  Dynamical Obstacle Avoidance of Task- Constrained Mobile Manipulation Using Model Predictive Control , 2019, IEEE Access.

[5]  Marco Hutter,et al.  ALMA - Articulated Locomotion and Manipulation for a Torque-Controllable Robot , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[6]  Gregory S. Chirikjian,et al.  Kinematic Analysis of Hexapod Manipulation , 2016 .

[7]  Dmitry Berenson,et al.  An optimization approach to planning for mobile manipulation , 2008, 2008 IEEE International Conference on Robotics and Automation.

[8]  Michael Murphy,et al.  Dynamic whole-body robotic manipulation , 2013, Defense, Security, and Sensing.

[9]  Joel W. Burdick,et al.  Kinematics and methods for combined quasi-static stance/reach planning in multi-limbed robots , 2014, 2014 IEEE International Conference on Robotics and Automation (ICRA).

[10]  Dilip Kumar Pratihar,et al.  Study on kinematics and inverse dynamics of legged mobile manipulator for determining feet-terrain reaction forces and joint torques , 2019 .

[11]  Tatsuo Arai,et al.  Hexapod with integrated limb mechanism of leg and arm , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[12]  Darwin G. Caldwell,et al.  Towards a multi-legged mobile manipulator , 2016, 2016 IEEE International Conference on Robotics and Automation (ICRA).

[13]  Michael Murphy,et al.  High degree-of-freedom dynamic manipulation , 2012, Defense, Security, and Sensing.

[14]  Oscar Lima,et al.  A Generic Optimization Based Cartesian Controller for Robotic Mobile Manipulation , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[15]  Dilip Kumar Pratihar,et al.  Design and Development of a Six-legged Mobile Manipulator for Education and Research (SiMMER) , 2019 .

[16]  Joel W. Burdick,et al.  Kinematics for combined quasi-static force and motion control in multi-limbed robots , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[17]  Ashish Dutta,et al.  Motion planning and redundancy resolution of a rover manipulator , 2015, 2015 IEEE International WIE Conference on Electrical and Computer Engineering (WIECON-ECE).