scholarly journals Using the Functional Reach Test for Probing the Static Stability of Bipedal Standing in Humanoid Robots Based on the Passive Motion Paradigm

2013 ◽  
Vol 2013 ◽  
pp. 1-8
Author(s):  
Jacopo Zenzeri ◽  
Dalia De Santis ◽  
Vishwanathan Mohan ◽  
Maura Casadio ◽  
Pietro Morasso
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
Static Stability ◽  
Reaching Movements ◽  
Whole Body ◽  
Passive Motion ◽  
Functional Reach ◽  
Functional Reach Test ◽  
Passive Motion Paradigm

The goal of this paper is to analyze the static stability of a computational architecture, based on the Passive Motion Paradigm, for coordinating the redundant degrees of freedom of a humanoid robot during whole-body reaching movements in bipedal standing. The analysis is based on a simulation study that implements the Functional Reach Test, originally developed for assessing the danger of falling in elderly people. The study is carried out in the YARP environment that allows realistic simulations with the iCub humanoid robot.

New 3-DOFs Hybrid Mechanism for Ankle and Wrist of Humanoid Robot: Modeling, Simulation, and Experiments

2011 ◽  
Vol 133 (2) ◽  
Author(s):  
Samer Alfayad ◽  
Fethi B. Ouezdou ◽  
Faycal Namoun
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Power Transmission ◽  
Mechanical Design ◽  
Humanoid Robots ◽  
Classical Solutions ◽  
Kinematic Modeling ◽  
New Class ◽  
Hybrid Mechanism ◽  
And Control

This paper deals with the design of a new class of hybrid mechanism dedicated to humanoid robotics application. Since the designing and control of humanoid robots are still open questions, we propose the use of a new class of mechanisms in order to face several challenges that are mainly the compactness and the high power to mass ratio. Human ankle and wrist joints can be considered more compact with the highest power capacity and the lowest weight. The very important role played by these joints during locomotion or manipulation tasks makes their design and control essential to achieve a robust full size humanoid robot. The analysis of all existing humanoid robots shows that classical solutions (serial or parallel) leading to bulky and heavy structures are usually used. To face these drawbacks and get a slender humanoid robot, a novel three degrees of freedom hybrid mechanism achieved with serial and parallel substructures with a minimal number of moving parts is proposed. This hybrid mechanism that is able to achieve pitch, yaw, and roll movements can be actuated either hydraulically or electrically. For the parallel submechanism, the power transmission is achieved, thanks to cables, which allow the alignment of actuators along the shin or the forearm main axes. Hence, the proposed solution fulfills the requirements induced by both geometrical, power transmission, and biomechanics (range of motion) constraints. All stages including kinematic modeling, mechanical design, and experimentation using the HYDROïD humanoid robot’s ankle mechanism are given in order to demonstrate the novelty and the efficiency of the proposed solution.

DYNAMIC ROLL-AND-RISE MOTION BY AN ADULT-SIZE HUMANOID ROBOT

2004 ◽  
Vol 01 (03) ◽  
pp. 497-516 ◽  
Author(s):  
YASUO KUNIYOSHI ◽  
YOSHIYUKI OHMURA ◽  
KOJI TERADA ◽  
AKIHIKO NAGAKUBO
Keyword(s):  
Critical Points ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
The Body ◽  
Whole Body ◽  
Adult Size ◽  
Constrained Motion ◽  
Goal State ◽  
Trade Offs ◽  
Alternative Approach

Whole-body dynamic actions under various contacts with the environment will be very important for future humanoid robots to support human tasks in unstructured environments. Such skills are very difficult to realize using the standard motion control methodology based on asymptotic convergence to the successive desired states. An alternative approach would be to exploit the passive dynamics of the body under constrained motion, and to navigate through multiple dynamics by imposing the least control in order to robustly reach the goal state. As a first example of such a strategy, we propose and investigate a "Roll-and-Rise" motion. This is a fully dynamic whole-body task including underactuated motion whose state trajectory is insoluble, and unpredictable perturbations due to complex contacts with the ground. First, we analyze the global structure of Roll-and-Rise motion. Then the critical points are analyzed using simplified models and simulations. The results suggest a non-uniform control strategy which focuses on sparse critical points in the global phase space, and allows deviations and trade-offs at other parts. Finally, experiments with a real adult-size humanoid robot are successfully carried out. The robot rose from a flat-lying posture to a crouching posture within 2 seconds.

scholarly journals Whole-Body Operational Space Control for Locomotion and Manipulation

2015 ◽  
Vol 137 (06) ◽  
pp. S2-S6
Author(s):  
Luis Sentis
Keyword(s):  
High Speed ◽  
Degrees Of Freedom ◽  
Humanoid Robots ◽  
Rigid Body Dynamics ◽  
Joint Torque ◽  
Whole Body ◽  
Operational Space ◽  
Body Dynamics ◽  
Service Oriented ◽  
High Level

This article discusses the various researches being undertaken to study and develop Whole-Body Operational Space Control (WBOSC). The WBOSC emerges as a capable framework for real-time unified control of motion and force of humanoid robots. It could theoretically outperform high-speed industrial manipulators while providing the grounds for new types of service-oriented applications that require contact, by exploiting the rigid body dynamics of systems. By relying on joint torque sensors, WBOSC opens up the potential to interact with the physical environment using any part of the robot’s body while regulating the effective mechanical impedances to safe values. With ControlIt!, the developers provide a strict and easy way to use the WBOSC API consisting of compound tasks which define the operational space, and constraint sets that define the contacts with the environment as well as dependent degrees of freedom. ControlIt! is easy to connect to high level planners.

Kinodynamic Planning for Humanoid Robots Walking on Uneven Terrain

2009 ◽  
Vol 21 (3) ◽  
pp. 311-316 ◽  
Author(s):  
Kensuke Harada ◽  
◽  
Mitsuharu Morisawa ◽  
Shin-ichiro Nakaoka ◽  
Kenji Kaneko ◽  
...  
Keyword(s):  
Humanoid Robot ◽  
Humanoid Robots ◽  
Pattern Generator ◽  
Body Motion ◽  
Whole Body ◽  
Gait Planning ◽  
Uneven Terrain ◽  
Walking Pattern ◽  
Dynamic Constraint ◽  
Dynamical Balance

For the purpose of realizing the humanoid robot walking on uneven terrain, this paper proposes the kinodynamic gait planning method where both kinematics and dynamics of the system are considered. We can simultaneously plan both the foot-place and the whole-body motion taking the dynamical balance of the robot into consideration. As a dynamic constraint, we consider the differential equation of the robot's CoG. To solve this constraint, we use a walking pattern generator. We randomly sample the configuration space to search for the path connecting the start and the goal configurations. To show the effectiveness of the proposed methods, we show simulation and experimental results where the humanoid robot HRP-2 walks on rocky cliff with hands contacting the environment.

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.

Recognizing Gestures for Humanoid Robot Using Proto-Symbol Space

2011 ◽  
Vol 403-408 ◽  
pp. 4769-4776
Author(s):  
Nitin Kumar ◽  
Suraj Prakash Sahu ◽  
Jay Prakash Maurya ◽  
G.C. Nandi ◽  
Pavan Chakraborty
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Nearest Neighbor ◽  
Humanoid Robots ◽  
K Nearest Neighbor ◽  
Symbol Space ◽  
Communication Method ◽  
Human Gestures ◽  
Distance Vector ◽  
Hand Gestures Recognition

This paper describes the non Verbal communication method for developing a gesture-based system using Mimesis model. The proposed method is applicable to any hand gesture represented by a multi-dimensional signal. The entire work concentrates mainly on hand gestures recognition. It develops a way to communicate between Humans and the Humanoid Robots through gestural medium. The Mimesis is the technique of performing human gestures through imitation, recognition and generation. Different Gestures are being converted into code words through the use of code book. These code words are then converted into Proto-Symbols, these proto symbol then forms basis for training of the Humanoid robot. The recognition part is performed through a “distance vector”, a novel algorithm developed by us which is a combination of Euclidean distance and K-nearest neighbor. The generation part is done through the use of WEBOTS which include use of Humanoid robot HOAP 2 having 25 degrees of freedom. All the process of training, recognition and generation are simulated through MATLAB.

Design of a Human-Like Range of Motion Hip Joint for Humanoid Robots

2014 ◽  
Author(s):  
Bryce Lee ◽  
Coleman Knabe ◽  
Viktor Orekhov ◽  
Dennis Hong
Keyword(s):  
Range Of Motion ◽  
Hip Joint ◽  
Disaster Response ◽  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Large Range ◽  
Humanoid Robots ◽  
Linkage Mechanism ◽  
Joint Torques ◽  
Similar Range

For a humanoid robot to have the versatility of humans, it needs to have similar motion capabilities. This paper presents the design of the hip joint of the Tactical Hazardous Operations Robot (THOR), which was created to perform disaster response duties in human-structured environments. The lower body of THOR was designed to have a similar range of motion to the average human. To accommodate the large range of motion requirements of the hip, it was divided into a parallel-actuated universal joint and a linkage-driven pin joint. The yaw and roll degrees of freedom are driven cooperatively by a pair of parallel series elastic linear actuators to provide high joint torques and low leg inertia. In yaw, the left hip can produce a peak of 115.02 [Nm] of torque with a range of motion of −20° to 45°. In roll, it can produce a peak of 174.72 [Nm] of torque with a range of motion of −30° to 45°. The pitch degree of freedom uses a Hoeken’s linkage mechanism to produce 100 [Nm] of torque with a range of motion of −120° to 30°.

scholarly journals Behaviour Generation in Humanoids by Learning Potential-Based Policies from Constrained Motion

2008 ◽  
Vol 5 (4) ◽  
pp. 195-211 ◽  
Author(s):  
Matthew Howard ◽  
Stefan Klanke ◽  
Michael Gienger ◽  
Christian Goerick ◽  
Sethu Vijayakumar
Keyword(s):  
Degrees Of Freedom ◽  
Humanoid Robot ◽  
Humanoid Robots ◽  
Movement Planning ◽  
Policy Learning ◽  
High Dimensional ◽  
Constrained Motion ◽  
Learning Potential ◽  
Kinematic Data ◽  
Motion Data

Movement generation that is consistent with observed or demonstrated behaviour is an efficient way to seed movement planning in complex, high-dimensional movement systems like humanoid robots. We present a method for learning potential-based policies from constrained motion data. In contrast to previous approaches to direct policy learning, our method can combine observations from a variety of contexts where different constraints are in force, to learn the underlying unconstrained policy in form of its potential function. This allows us to generalise and predict behaviour where novel constraints apply. We demonstrate our approach on systems of varying complexity, including kinematic data from the ASIMO humanoid robot with 22 degrees of freedom.

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