WHOLE-BODY COOPERATIVE BALANCED MOTION GENERATION FOR REACHING

2005 ◽  
Vol 02 (04) ◽  
pp. 437-457 ◽  
Author(s):  
KOICHI NISHIWAKI ◽  
MAMORU KUGA ◽  
SATOSHI KAGAMI ◽  
MASAYUKI INABA ◽  
HIROCHIKA INOUE
Keyword(s):  
Visual Information ◽  
Degrees Of Freedom ◽  
Dynamic Balance ◽  
Construction Method ◽  
Body Motion ◽  
Whole Body ◽  
Motion Generation ◽  
Final Goal ◽  
Posture Selection

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.

Efficient ZMP Formulation and Effective Whole-Body Motion Generation for a Human-Like Mechanism

2008 ◽  
Author(s):  
Joo H. Kim ◽  
Yujiang Xiang ◽  
Rajankumar Bhatt ◽  
Jingzhou Yang ◽  
Hyun-Joon Chung ◽  
...  
Keyword(s):  
Dynamic Balance ◽  
Body Motion ◽  
Whole Body ◽  
Motion Generation ◽  
Standing Posture ◽  
Upright Standing ◽  
Task Requirements ◽  
Reaction Forces ◽  
Zero Moment ◽  
Physics Based Simulation

An approach of generating dynamic biped motions of a human-like mechanism is proposed. An alternative and efficient formulation of the Zero-Moment Point for dynamic balance and the approximated ground reaction forces/moments are derived from the resultant reaction loads, which includes the gravity, the externally applied loads, and the inertia. The optimization problem is formulated to address the redundancy of the human task, where the general biped and task-specific constraints are imposed depending on the task requirements. The proposed method is fully predictive and generates physically feasible human-like motions from scratch; it does not require any input reference from motion capture or animation. The resulting generated motions demonstrate how a human-like mechanism reacts effectively to different external load conditions in performing a given task by showing realistic features of cause and effect. In addition, the energy-optimality of the upright standing posture is numerically verified among infinite feasible static biped postures without self contact. The proposed formulation is beneficial to motion planning, control, and physics-based simulation of humanoids and human models.

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.

scholarly journals Compliant Humanoids Moving Toward Rehabilitation Applications: Transparent Integration of Real-Time Control, Whole-Body Motion Generation, and Virtual Reality

2019 ◽  
Vol 26 (4) ◽  
pp. 83-93
Author(s):  
Pouya Mohammadi ◽  
Enrico Mingo Hoffman ◽  
Niels Dehio ◽  
Milad S. Malekzadeh ◽  
Martin Giese ◽  
...  
Keyword(s):  
Virtual Reality ◽  
Real Time ◽  
Body Motion ◽  
Whole Body ◽  
Motion Generation ◽  
Real Time Control ◽  
Time Control

Whole-Body Human-to-Humanoid Motion Imitation

2013 ◽  
Vol 479-480 ◽  
pp. 617-621
Author(s):  
Hsien I Lin ◽  
Zan Sheng Chen
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Optimal Solution ◽  
Human Motion ◽  
Body Motion ◽  
Upper Body ◽  
Whole Body ◽  
Nao Robot ◽  
Novel Approach ◽  
Intuitive Method

Human-to-Humanoid motion imitation is an intuitive method to teach a humanoid robot how to act by human demonstration. For example, teaching a robot how to stand is simply showing the robot how a human stands. Much of previous work in motion imitation focuses on either upper-body or lower-body motion imitation. In this paper, we propose a novel approach to imitate human whole-body motion by a humanoid robot. The main problem of the proposed work is how to control robot balance and keep the robot motion as similar as taught human motion simultaneously. Thus, we propose a balance criterion to assess how well the root can balance and use the criterion and a genetic algorithm to search a sub-optimal solution, making the root balanced and its motion similar to human motion. We have validated the proposed work on an Aldebaran Robotics NAO robot with 25 degrees of freedom. The experimental results show that the root can imitate human postures and autonomously keep itself balanced.

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