On-Site Locomotion Planning for a Humanoid Robot with Stable Whole-Body Collision Avoidance Motion Guided by Footsteps and Centroidal Trajectory

2019 ◽  
Vol 17 (01) ◽  
pp. 1950035
Author(s):  
Iori Kumagai ◽  
Mitsuharu Morisawa ◽  
Shin’ichiro Nakaoka ◽  
Fumio Kanehiro
Keyword(s):  
Motion Planning ◽  
Collision Avoidance ◽  
Dynamic Simulation ◽  
Inverse Kinematics ◽  
Humanoid Robot ◽  
Computational Cost ◽  
Body Motion ◽  
Whole Body ◽  
Planning Framework ◽  
Narrow Space

In this paper, we propose a locomotion planning framework for a humanoid robot with stable whole-body collision avoidance motion, which enables the robot to traverse an unknown narrow space on the spot based on environmental measurements. The key idea of the proposed method is to reduce a large computational cost for the whole-body locomotion planning by utilizing global footstep planning results and its centroidal trajectory as a guide. In the global footstep planning phase, we modify the bounding box of the robot approximating the centroidal sway amplitude of the candidate footsteps. This enables the planner to obtain appropriate footsteps and transition time for next whole-body motion planning. Then, we execute sequential whole-body motion planning by prioritized inverse kinematics considering collision avoidance and maintaining its ZMP trajectory, which enables the robot to plan stable motion for each step in 223[Formula: see text]ms at worst. We evaluated the proposed framework by a humanoid robot HRP-5P in the dynamic simulation and the real world. The major contribution of our paper is solving the problem of increasing computational cost for whole-body motion planning and enabling a humanoid robot to execute adaptive on-site locomotion planning in an unknown narrow space.

scholarly journals Sampling-Based Motion Planning for Free-Floating Space Robot without Inverse Kinematics

2020 ◽  
Vol 10 (24) ◽  
pp. 9137
Author(s):  
Hongwen Zhang ◽  
Zhanxia Zhu
Keyword(s):  
Motion Planning ◽  
Inverse Kinematics ◽  
Random Trees ◽  
Space Robot ◽  
Initial Configuration ◽  
First Order ◽  
System A ◽  
Planning Framework ◽  
Planning Algorithm ◽  
Differential Relationship

Motion planning is one of the most important technologies for free-floating space robots (FFSRs) to increase operation safety and autonomy in orbit. As a nonholonomic system, a first-order differential relationship exists between the joint angle and the base attitude of the space robot, which makes it pretty challenging to implement the relevant motion planning. Meanwhile, the existing planning framework must solve inverse kinematics for goal configuration and has the limitation that the goal configuration and the initial configuration may not be in the same connected domain. Thus, faced with these questions, this paper investigates a novel motion planning algorithm based on rapidly-exploring random trees (RRTs) for an FFSR from an initial configuration to a goal end-effector (EE) pose. In a motion planning algorithm designed to deal with differential constraints and restrict base attitude disturbance, two control-based local planners are proposed, respectively, for random configuration guiding growth and goal EE pose-guiding growth of the tree. The former can ensure the effective exploration of the configuration space, and the latter can reduce the possibility of occurrence of singularity while ensuring the fast convergence of the algorithm and no violation of the attitude constraints. Compared with the existing works, it does not require the inverse kinematics to be solved while the planning task is completed and the attitude constraint is preserved. The simulation results verify the effectiveness of the algorithm.

Whole-Body Motion Planning

2018 ◽  
pp. 1575-1599 ◽  
Author(s):  
Eiichi Yoshida ◽  
Fumio Kanehiro ◽  
Jean-Paul Laumond
Keyword(s):  
Motion Planning ◽  
Body Motion ◽  
Whole Body

scholarly journals Efficient Planning of Humanoid Motions by Modifying Constraints

2013 ◽  
Vol 4 (1) ◽  
Author(s):  
ChangHyun Sung ◽  
Takahiro Kagawa ◽  
Yoji Uno
Keyword(s):  
Motion Planning ◽  
Sufficient Conditions ◽  
Computation Time ◽  
Humanoid Robots ◽  
Body Motion ◽  
Whole Body ◽  
Planning Problem ◽  
Point Representation ◽  
Efficient Planning ◽  
Unpredictable Environment

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.

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

2019 ◽  
Author(s):  
Kondalarao Bhavanibhatla ◽  
Sulthan Suresh-Fazeela ◽  
Dilip Kumar Pratihar
Keyword(s):  
Motion Planning ◽  
Degrees Of Freedom ◽  
Robotic System ◽  
Simulation Software ◽  
Body Motion ◽  
Whole Body ◽  
Mobile Manipulator ◽  
Coordinated Motion ◽  
Multibody Dynamic ◽  
The Given

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.

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