scholarly journals Task-oriented whole-body planning for humanoids based on hybrid motion generation

2014 ◽  
Author(s):  
Marco Cognetti ◽  
Pouya Mohammadi ◽  
Giuseppe Oriolo ◽  
Marilena Vendittelli
Keyword(s):  
Whole Body ◽  
Motion Generation ◽  
Hybrid Motion ◽  
Task Oriented

scholarly journals Real-Time Whole-Body Imitation by Humanoid Robots and Task-Oriented Teleoperation Using an Analytical Mapping Method and Quantitative Evaluation

2018 ◽  
Vol 8 (10) ◽  
pp. 2005 ◽  
Author(s):  
Zhijun Zhang ◽  
Yaru Niu ◽  
Ziyi Yan ◽  
Shuyang Lin
Keyword(s):  
Real Time ◽  
Humanoid Robots ◽  
Mapping Method ◽  
Whole Body ◽  
Mode Switching ◽  
Natural Mode ◽  
And Performance ◽  
Virtual Joints ◽  
Task Oriented ◽  
And Task

Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable whole-body imitation and task-oriented teleoperation via imitation are challenging issues. In this paper, a novel comprehensive and unrestricted real-time whole-body imitation system for humanoid robots is designed and developed. To map human motions to a robot, an analytical method called geometrical analysis based on link vectors and virtual joints (GA-LVVJ) is proposed. In addition, a real-time locomotion method is employed to realize a natural mode of operation. To achieve safe mode switching, a filter strategy is proposed. Then, two quantitative vector-set-based methods of similarity evaluation focusing on the whole body and local links, called the Whole-Body-Focused (WBF) method and the Local-Link-Focused (LLF) method, respectively, are proposed and compared. Two experiments conducted to verify the effectiveness of the proposed methods and system are reported. Specifically, the first experiment validates the good stability and similarity features of our system, and the second experiment verifies the effectiveness with which complicated tasks can be executed. At last, an imitation learning mechanism in which the joint angles of demonstrators are mapped by GA-LVVJ is presented and developed to extend the proposed system.

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.

scholarly journals Real-Time Whole-Body Imitation by Humanoid Robots and Task-Oriented Teleoperation Using an Analytical Mapping Method and Quantitative Evaluation

2018 ◽  
Author(s):  
Zhijun Zhang ◽  
Yaru Niu ◽  
Ziyi Yan ◽  
Shuyang Lin
Keyword(s):  
Real Time ◽  
Humanoid Robots ◽  
Mapping Method ◽  
Whole Body ◽  
Mode Switching ◽  
Natural Mode ◽  
And Performance ◽  
Virtual Joints ◽  
Task Oriented ◽  
And Task

Due to the limitations on the capabilities of current robots regarding task learning and performance, imitation is an efficient social learning approach that endows a robot with the ability to transmit and reproduce human postures, actions, behaviors, etc., as a human does. Stable whole-body imitation and task-oriented teleoperation via imitation are challenging issues. In this paper, a novel comprehensive and unrestricted real-time whole-body imitation system for humanoid robots is designed and developed. To map human motions to a robot, an analytical method called geometrical analysis based on link vectors and virtual joints (GA-LVVJ) is proposed. In addition, a real-time locomotion method is employed to realize a natural mode of operation. To achieve safe mode switching, a filter strategy is proposed. Then, two quantitative vector-set-based methods of similarity evaluation focusing on the whole body and local links, called the Whole-Body-Focused (WBF) method and the Local-Link-Focused (LLF) method, respectively, are proposed and compared. Two experiments conducted to verify the effectiveness of the proposed methods and system are reported. Specifically, the first experiment validates the good stability and similarity features of our system, and the second experiment verifies the effectiveness with which complicated tasks can be executed. At last, an imitation learning mechanism in which the joint angles of demonstrators are mapped by GA-LVVJ is presented and developed to extend the proposed 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.

Pushing and pulling motion generation for humanoid robots using whole-body momentum control based on analytical inverse kinematics

2020 ◽  
Vol 34 (21-22) ◽  
pp. 1442-1454
Author(s):  
Yuya Hakamata ◽  
Satoki Tsuichihara ◽  
Gustavo Alfonso Garcia Ricardez ◽  
Jun Takamatsu ◽  
Tsukasa Ogasawara
Keyword(s):  
Inverse Kinematics ◽  
Humanoid Robots ◽  
Whole Body ◽  
Motion Generation ◽  
Pushing And Pulling
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