Dynamics and Simulation of General Human and Humanoid Motion in Sports

This chapter relates biomechanics to robotics. The mathematical models are derived to cover the kinematics and dynamics of virtually any motion of a human or a humanoid robot. Benefits for humanoid robots are seen in fully dynamic control and a general simulator for the purpose of system designing and motion planning. Biomechanics in sports and medicine can use these as a tool for mathematical analysis of motion and disorders. Better results in sports and improved diagnostics are foreseen. This work is a step towards the biologically-inspired robot control needed for a diversity of tasks expected in humanoids, and robotic assistive devices helping people to overcome disabilities or augment their physical potentials. This text deals mainly with examples coming from sports in order to justify this aspect of research.

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Humans and humanoids

10.1093/oso/9780199674923.003.0047 ◽

2018 ◽

Author(s):

Giorgio Metta

Keyword(s):

Humanoid Robot ◽

Robot Vision ◽

Physical Space ◽

Humanoid Robots ◽

Human Robot Interaction ◽

Biologically Inspired ◽

Robot Interaction ◽

Humanoid Robotics ◽

Biomimetic Robot ◽

Compliant Actuation

This chapter outlines a number of research lines that, starting from the observation of nature, attempt to mimic human behavior in humanoid robots. Humanoid robotics is one of the most exciting proving grounds for the development of biologically inspired hardware and software—machines that try to recreate billions of years of evolution with some of the abilities and characteristics of living beings. Humanoids could be especially useful for their ability to “live” in human-populated environments, occupying the same physical space as people and using tools that have been designed for people. Natural human–robot interaction is also an important facet of humanoid research. Finally, learning and adapting from experience, the hallmark of human intelligence, may require some approximation to the human body in order to attain similar capacities to humans. This chapter focuses particularly on compliant actuation, soft robotics, biomimetic robot vision, robot touch, and brain-inspired motor control in the context of the iCub humanoid robot.

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Supervoxel Plane Segmentation and Multi-Contact Motion Generation for Humanoid Stair Climbing

International Journal of Humanoid Robotics ◽

10.1142/s0219843616500225 ◽

2017 ◽

Vol 14 (01) ◽

pp. 1650022 ◽

Cited By ~ 6

Author(s):

Tianwei Zhang ◽

Stéphane Caron ◽

Yoshihiko Nakamura

Keyword(s):

Motion Planning ◽

Humanoid Robot ◽

Real Life ◽

Estimation Method ◽

Humanoid Robots ◽

Stair Climbing ◽

Lidar Data ◽

Motion Generation ◽

Prior Models ◽

Motion Generator

Stair climbing is still a challenging task for humanoid robots, especially in unknown environments. In this paper, we address this problem from perception to execution. Our first contribution is a real-time plane-segment estimation method using Lidar data without prior models of the staircase. We then integrate this solution with humanoid motion planning. Our second contribution is a stair-climbing motion generator where estimated plane segments are used to compute footholds and stability polygons. We evaluate our method on various staircases. We also demonstrate the feasibility of the generated trajectories in a real-life experiment with the humanoid robot HRP-4.

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First human–robot archery competition: a new humanoid robot challenge

The Knowledge Engineering Review ◽

10.1017/s026988892000003x ◽

2020 ◽

Vol 35 ◽

Author(s):

Kuo-Yang Tu ◽

Hong-Yu Lin ◽

You-Ru Li ◽

Che-Ping Hung ◽

Jacky Baltes

Keyword(s):

Motion Planning ◽

Humanoid Robot ◽

Humanoid Robots ◽

Special Design ◽

Design And Development ◽

Trade Off ◽

Design And Implementation ◽

Structure And Motion ◽

Further Development

Abstract A humanoid robot developed to play multievent athletes like human has paved a way for interesting and popular robotics research. One of the great dreams is to develop a humanoid robot being able to challenge human athletes. Therefore, the challenge of humanoid robots to play archery against human is organized at Taichung, Taiwan, in HuroCup, FIRA 2018, on August 7th. The difficulties of developing humanoid robot are not just on playing archery. The humanoid robots for HuroCup must make use of the same hardware for the 10 events. In this paper, the design and implementation of the humanoid robot for archery are proposed under the trade off with other nine events. Therefore, the humanoid robot must have some special design and development on software. More specially, the humanoid robot must use professional bow to challenge human for archery competition. Therefore, in this paper, special shooting posture under constrained arm structure and motion planning of both arms for more torque to play professional bow are proposed. In addition, the further development of humanoid robot to improve archery shooting is summarized.

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Design and Operation of Humanoid Robots with Incipient Fall Detection

Proceedings of Higher Educational Institutions Маchine Building ◽

10.18698/0536-1044-2021-1-11-15 ◽

2021 ◽

pp. 11-15

Author(s):

M. Ceccarelli

Keyword(s):

Motion Planning ◽

Rational Design ◽

Humanoid Robot ◽

Fall Detection ◽

Humanoid Robots ◽

Design Issues ◽

Detection Function ◽

Design Solutions

Falling is one of the main reasons of failure and damage of humanoid robots when they perform human-like tasks. Fall detection can be used not only to prevent damage to the humanoid robot when falling but also to adjust its actions so that the operation can run continuously. The paper discusses design issues, analyses the fall detection function and diagnostics sensors, and proposes rational design solutions for the required motion planning.

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Motion planning for humanoid robot dynamically stepping over consecutive large obstacles

Industrial Robot the international journal of robotics research and application ◽

10.1108/ir-08-2015-0157 ◽

2016 ◽

Vol 43 (2) ◽

pp. 204-220 ◽

Cited By ~ 3

Author(s):

Fayong Guo ◽

Tao Mei ◽

Minzhou Luo ◽

Marco Ceccarelli ◽

Ziyi Zhao ◽

...

Keyword(s):

Motion Planning ◽

Trajectory Planning ◽

Humanoid Robot ◽

Extreme Case ◽

Humanoid Robots ◽

Decision Criterion ◽

Body Motion ◽

Feasibility Analysis ◽

Upper Body ◽

Content Type

Purpose – Humanoid robots should have the ability of walking in complex environment and overcoming large obstacles in rescue mission. Previous research mainly discusses the problem of humanoid robots stepping over or on/off one obstacle statically or dynamically. As an extreme case, this paper aims to demonstrate how the robots can step over two large obstacles continuously. Design/methodology/approach – The robot model uses linear inverted pendulum (LIP) model. The motion planning procedure includes feasibility analysis with constraints, footprints planning, legs trajectory planning with collision-free constraint, foot trajectory adapter and upper body motion planning. Findings – The motion planning with the motion constraints is a key problem, which can be considered as global optimization issue with collision-free constraint, kinematic limits and balance constraint. With the given obstacles, the robot first needs to determine whether it can achieve stepping over, if feasible, and then the robot gets the motion trajectory for the legs, waist and upper body using consecutive obstacles stepping over planning algorithm which is presented in this paper. Originality/value – The consecutive stepping over problem is proposed in this paper. First, the paper defines two consecutive stepping over conditions, sparse stepping over (SSO) and tight stepping over (TSO). Then, a novel feasibility analysis method with condition (SSO/TSO) decision criterion is proposed for consecutive obstacles stepping over. The feasibility analysis method’s output is walking parameters with obstacles’ information. Furthermore, a modified legs trajectory planning method with center of mass trajectory compensation using upper body motion is proposed. Finally, simulations and experiments for SSO and TSO are carried out by using the XT-I humanoid robot platform with the aim to verify the validity and feasibility of the novel methods proposed in this paper.

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THE CHALLENGE OF MOTION PLANNING FOR SOCCER PLAYING HUMANOID ROBOTS

International Journal of Humanoid Robotics ◽

10.1142/s0219843608001480 ◽

2008 ◽

Vol 05 (03) ◽

pp. 481-499 ◽

Cited By ~ 6

Author(s):

STEFANO CARPIN ◽

MARCELO KALLMANN ◽

ENRICO PAGELLO

Keyword(s):

Motion Planning ◽

Humanoid Robot ◽

State Of The Art ◽

Humanoid Robots ◽

Soccer Players ◽

Double Support ◽

Short And Long Term ◽

Art Research ◽

Key Aspects

Motion planning for humanoids faces several challenging issues: high dimensionality of the configuration space, necessity to address balance constraints in single and double support mode, higher levels of planning for coordination of different skills, etc. While the above challenges hold for any humanoid robot, the soccer scenario adds difficulties rarely addressed in humanoid motion planning research, as for example: dynamic environments with active opponents, the requirement to perform short- and long-term plans for performing soccer-relevant actions, and the necessity to plan movements purposely terminating with a collision with the ball. These aspects open a completely new scenario for researchers. This paper surveys state-of-the-art research in motion planning for humanoid robots with a focus on outlining connections, differences, and identifying the key aspects that ought to be addressed when developing effective humanoid soccer players.

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Contribution to the dynamic study of humanoid robots interacting with dynamic environment

Robotica ◽

10.1017/s0263574704000207 ◽

2004 ◽

Vol 22 (4) ◽

pp. 439-447 ◽

Cited By ~ 8

Author(s):

Miomir Vukobratović ◽

Veljko Potkonjak ◽

Aleksandar Rodić

Keyword(s):

Mathematical Models ◽

Dynamic Control ◽

Dynamic Environment ◽

Dynamic Modelling ◽

Control Unit ◽

Humanoid Robots ◽

The Other ◽

Unresolved Issue ◽

On Line ◽

General Answer

The questions when and why one needs to use mathematical models, and especially the models of dynamics, represent still an unresolved issue. A general answer would be that dynamic modelling is needed as a tool when designing structure of the system and its control unit. In this case we talk about simulation. The other application is in on-line control of the system – the so-called dynamic control. While in simulation one generally uses the best available model, the control can be based on a reduced dynamics, depending on a particular task. The aim of this paper was to highlight the problems important for the dynamics of humanoids and their dynamic environment.

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BALANCE MOTION PLANNING FOR HUMANOID ROBOT BASED ON 3D INVERTED PENDULUM MODEL

Journal of Science and Technology - IUH ◽

10.46242/jstiuh.v36i03.4078 ◽

2022 ◽

Vol 36 (06) ◽

Author(s):

DUONG MIEN KA ◽

TRAN HUU TOAN

Keyword(s):

Motion Planning ◽

Dynamic Model ◽

Humanoid Robot ◽

Inverted Pendulum ◽

Humanoid Robots ◽

The Other ◽

Three Dimension ◽

Inverted Pendulum Model ◽

Pendulum Model

Researches on humanoid robots are alway attractive to many researchers in robotics field. One of considerable challenges of humanoid robots is to keep balance and stability of their movement. Because a humanoid robot moves by two legs, most of time of the step period of the humanoid robot is be in one leg touching on the floor and the other leg swinging forward. This posture is similar to a three dimension (3D) inverted pendulum model. This papers presents the dynamic model of a 3D inverted pendulum model and applies to balanced motion planning for a humanoid robot. The obtained results show that the robot is able to keep balance during its movements

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A Multitasking-Oriented Robot Arm Motion Planning Scheme Based on Deep Reinforcement Learning and Twin Synchro-Control

Sensors ◽

10.3390/s20123515 ◽

2020 ◽

Vol 20 (12) ◽

pp. 3515 ◽

Cited By ~ 2

Author(s):

Chuzhao Liu ◽

Junyao Gao ◽

Yuanzhen Bi ◽

Xuanyang Shi ◽

Dingkui Tian

Keyword(s):

Reinforcement Learning ◽

Motion Planning ◽

Data Acquisition ◽

Humanoid Robot ◽

Data Acquisition System ◽

Humanoid Robots ◽

Acquisition System ◽

Robot Arm ◽

Digital Twin ◽

Angle Data

Humanoid robots are equipped with humanoid arms to make them more acceptable to the general public. Humanoid robots are a great challenge in robotics. The concept of digital twin technology complies with the guiding ideology of not only Industry 4.0, but also Made in China 2025. This paper proposes a scheme that combines deep reinforcement learning (DRL) with digital twin technology for controlling humanoid robot arms. For rapid and stable motion planning for humanoid robots, multitasking-oriented training using the twin synchro-control (TSC) scheme with DRL is proposed. For switching between tasks, the robot arm training must be quick and diverse. In this work, an approach for obtaining a priori knowledge as input to DRL is developed and verified using simulations. Two simple examples are developed in a simulation environment. We developed a data acquisition system to generate angle data efficiently and automatically. These data are used to improve the reward function of the deep deterministic policy gradient (DDPG) and quickly train the robot for a task. The approach is applied to a model of the humanoid robot BHR-6, a humanoid robot with multiple-motion mode and a sophisticated mechanical structure. Using the policies trained in the simulations, the humanoid robot can perform tasks that are not possible to train with existing methods. The training is fast and allows the robot to perform multiple tasks. Our approach utilizes human joint angle data collected by the data acquisition system to solve the problem of a sparse reward in DRL for two simple tasks. A comparison with simulation results for controllers trained using the vanilla DDPG show that the designed controller developed using the DDPG with the TSC scheme have great advantages in terms of learning stability and convergence speed.

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