Coordinated Motion Planning of Legged Mobile Manipulator for Tracking the Given End-Effector’s Trajectory

Author(s):  
Kondalarao Bhavanibhatla ◽  
Sulthan Suresh-Fazeela ◽  
Dilip Kumar Pratihar

Abstract In this paper, a novel algorithm is presented to achieve the coordinated motion planning of a Legged Mobile Manipulator (LMM) for tracking the given end-effector’s trajectory. LMM robotic system can be obtained by mounting a manipulator on the top of a multi-legged platform for achieving the capabilities of both manipulation and mobility. To exploit the advantages of these capabilities, the manipulator should be able to accomplish the task, while the hexapod platform moves simultaneously. In the presented approach, the whole-body motion planning is achieved in two steps. In the first step, the robotic system is assumed to be a mobile manipulator, in which the manipulator has two additional translational degrees of freedom at the base. The redundancy of this robotic system is solved by treating it as an optimization problem. Then, in the second step, the omnidirectional motion of the legged platform is achieved with a combination of straight forward and crab motions. The proposed algorithm is tested through a numerical simulation in MATLAB and then, validated on a virtual model of the robot using multibody dynamic simulation software, MSC ADAMS. Multiple trajectories of the end-effector have been tested and the results show that the proposed algorithm accomplishes the given task successfully by providing a singularity-free whole-body motion.

2018 ◽  
pp. 1575-1599 ◽  
Author(s):  
Eiichi Yoshida ◽  
Fumio Kanehiro ◽  
Jean-Paul Laumond

Author(s):  
ChangHyun Sung ◽  
Takahiro Kagawa ◽  
Yoji Uno

AbstractIn this paper, we propose an effective planning method for whole-body motions of humanoid robots under various conditions for achieving the task. In motion planning, various constraints such as range of motion have to be considered. Specifically, it is important to maintain balance in whole-body motion. In order to be useful in an unpredictable environment, rapid planning is an essential problem. In this research, via-point representation is used for assigning sufficient conditions to deal with various constraints in the movement. The position, posture and velocity of the robot are constrained as a state of a via-point. In our algorithm, the feasible motions are planned by modifying via-points. Furthermore, we formulate the motion planning problem as a simple iterative method with a Linear Programming (LP) problem for efficiency of the motion planning. We have applied the method to generate the kicking motion of a HOAP-3 humanoid robot. We confirmed that the robot can successfully score a goal with various courses corresponding to changing conditions of the location of an obstacle. The computation time was less than two seconds. These results indicate that the proposed algorithm can achieve efficient motion planning.


2019 ◽  
Vol 118 ◽  
pp. 263-277
Author(s):  
Hari Teja K. ◽  
Abhilash Balachandran ◽  
S.V. Shah

2013 ◽  
Vol 32 (9-10) ◽  
pp. 1089-1103 ◽  
Author(s):  
Sébastien Dalibard ◽  
Antonio El Khoury ◽  
Florent Lamiraux ◽  
Alireza Nakhaei ◽  
Michel Taïx ◽  
...  

Author(s):  
Bin Du ◽  
Jing Zhao ◽  
Chunyu Song

A mobile manipulator typically consists of a mobile platform and a robotic manipulator mounted on the platform. The base placement of the platform has a great influence on whether the manipulator can perform a given task. In view of the issue, a new approach to optimize the base placement for a specified task is proposed in this paper. Firstly, the workspace of a redundant manipulator is investigated. The manipulation capability of the redundant manipulator is maximized based on the manipulability index through the joint self-motion of the redundant manipulator. Then the maximum manipulation capability in the specified work point is determined. Next, the relative manipulability index (RMI) is defined for analyzing manipulation capability of the manipulator in its workspace, and the global manipulability map (GMM) is presented based on the above measure. Moreover, the optimal base placement related to the given task is obtained, and the motion planning is implemented by an improved rapidly-exploring random tree (RRT) algorithm with the RMI, which can enhance the manipulation capability from the initial point to the target point. Finally, the feasibility of the proposed algorithm is illustrated with numerical simulations and experiments on the mobile manipulator.


2005 ◽  
Vol 02 (04) ◽  
pp. 437-457 ◽  
Author(s):  
KOICHI NISHIWAKI ◽  
MAMORU KUGA ◽  
SATOSHI KAGAMI ◽  
MASAYUKI INABA ◽  
HIROCHIKA INOUE

This paper addresses a construction method of a system that realizes whole body reaching motion of humanoids. Humanoids have many redundant degrees of freedom for reaching, and even the base can be moved by making the robot step. Therefore, there are infinite final posture solutions for a final goal position of reaching, and there are also infinite solutions for reaching trajectories that realize a final reaching posture. It is, however, difficult to find an appropriate solution because of the constraint of dynamic balance, and relatively narrow movable range for each joint. We prepared basic postures heuristically, and a final reaching posture is generated by modifying one of them. Heuristics, such as the fact that kneeling down is suitable for reaching near the ground, can be implemented easily by using this method. Methods that compose the reaching system, that is, basic posture selection, modification of postures for generating final reaching postures, balance compensation, footstep planning to realize desired feet position, and generation and execution of whole body motion to final reaching postures are described. Reaching to manually set positions and picking up a bat at various postures using visual information are shown as experiments to show the performance of the system.


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