Inverse Solution and Optimal Concept Rethink from Human Operation to Industrial Redundant Manipulator

2014 ◽  
Vol 541-542 ◽  
pp. 1140-1145 ◽  
Author(s):  
Mei Ling Wang ◽  
Min Zhou Luo ◽  
Xin Lin
Keyword(s):  
Real Time ◽  
Computational Efficiency ◽  
Inverse Kinematics ◽  
Joint Angle ◽  
Inverse Solution ◽  
Joint Movement ◽  
Redundant Manipulator ◽  
Joint Angles ◽  
Human Arm ◽  
Dual Arm

More and more dual arm robots with redundant manipulator are introduced in industrial fields. Here we focus on this special structure with 7-DOF redundant manipulator, an exhibit analytical and optimal concept was proposed. The formula derivations of inverse kinematics showed that when the redundant joint angle has been obtained, the remaining six joint angles can be derived analytically, and there are eight sets of inverse solution for one giving redundant joint angle. Reversed thinking the joint movement habits, patterns, and frequency of human arm operations, an optimal concept was presented to gain a real time computational efficiency of a direct inverse solution while also achieving the purpose of application.

Dual arm-angle parameterisation and its applications for analytical inverse kinematics of redundant manipulators

Robotica ◽  
2015 ◽  
Vol 34 (12) ◽  
pp. 2669-2688 ◽  
Author(s):  
Wenfu Xu ◽  
Lei Yan ◽  
Zonggao Mu ◽  
Zhiying Wang
Keyword(s):  
Inverse Kinematics ◽  
Reference Plane ◽  
Redundant Manipulators ◽  
Redundant Manipulator ◽  
Singularity Problem ◽  
Human Arm ◽  
Angle Method ◽  
Self Motion ◽  
Dual Arm ◽  
Configuration Control

SUMMARYAn S-R-S (Spherical-Revolute-Spherical) redundant manipulator is similar to a human arm and is often used to perform dexterous tasks. To solve the inverse kinematics analytically, the arm-angle was usually used to parameterise the self-motion. However, the previous studies have had shortcomings; some methods cannot avoid algorithm singularity and some are unsuitable for configuration control because they use a temporary reference plane. In this paper, we propose a method of analytical inverse kinematics resolution based on dual arm-angle parameterisation. By making use of two orthogonal vectors to define two absolute reference planes, we obtain two arm angles that satisfy a specific condition. The algorithm singularity problem is avoided because there is always at least one arm angle to represent the redundancy. The dual arm angle method overcomes the shortcomings of traditional methods and retains the advantages of the arm angle. Another contribution of this paper is the derivation of the absolute reference attitude matrix, which is the key to the resolution of analytical inverse kinematics but has not been previously addressed. The simulation results for typical cases that include the algorithm singularity condition verified our method.

scholarly journals Learning of Obstacle Avoidance with Redundant Manipulator by Hierarchical SOM

2011 ◽  
Vol 15 (5) ◽  
pp. 525-531
Author(s):  
Yuichi Kobayashi ◽  
◽  
Takahiro Nomura
Keyword(s):  
Reinforcement Learning ◽  
Obstacle Avoidance ◽  
Inverse Kinematics ◽  
Joint Angle ◽  
Hand Position ◽  
Redundant Manipulator ◽  
Motion Generation ◽  
Joint Angles ◽  
Vision Sensors ◽  
Configuration Information

This paper proposes a method of obstacle avoidance motion generation for a redundant manipulator with a Self-OrganizingMap (SOM) and reinforcement learning. To consider redundancy, two types of SOMs - a hand position map and a joint angle map - are combined. Multiple joint angles corresponding to the same hand position are memorized in the proposed map. Preserved redundant configuration information is used to generate motions based on tasks and situations, while resolving inverse kinematics problems with a redundant manipulator. The proposed map is applied to planning motion control using reinforcement learning in an unknown environment, where collision with obstacles is detected only directly by tactile sensing. The feasibility of the proposed framework was verified by simulation and experiments with an arm robot with force and a vision sensors.

Joint angle variations analyses of the two link planar manipulator in welding by using inverse kinematics

Robotica ◽  
2005 ◽  
Vol 24 (3) ◽  
pp. 355-363 ◽  
Author(s):  
S. Bulut ◽  
M. B. Terzioǧlu
Keyword(s):  
Angular Velocity ◽  
Data Collection ◽  
Inverse Kinematics ◽  
Joint Angle ◽  
Joint Angles ◽  
End Effector ◽  
Fortran 90

In this paper, the joint angles of a two link planar manipulator are calculated by using inverse kinematics equations together with some geometric equalities. For a given position of the end-effector the joint angle and angular velocity of the links are derived. The analyses contains many equations which have to be solved. However, the solutions are rather cumbersome and complicated, therefore a program is written in Fortran 90 in order to do, the whole calculation and data collection. The results are given at the end of this paper.

scholarly journals Real-Time Inverse Kinematics of the Human Arm

1996 ◽  
Vol 5 (4) ◽  
pp. 393-401 ◽  
Author(s):  
Deepak Tolani ◽  
Norman I. Badler
Keyword(s):  
Closed Form ◽  
Real Time ◽  
Upper Bound ◽  
Multiple Solutions ◽  
Inverse Kinematics ◽  
Additional Constraint ◽  
Degree Of Freedom ◽  
Empirical Results ◽  
Human Arm ◽  
Real Time Applications

A simple inverse kinematics procedure is proposed for a seven degree of freedom model of the human arm. Two schemes are used to provide an additional constraint leading to closed-form analytical equations with an upper bound of two or four solutions, Multiple solutions can be evaluated on the basis of their proximity from the rest angles or the previous configuration of the arm. Empirical results demonstrate that the procedure is well suited for real-time applications.

Quick Motion Path Plan for Joint-Robot to Pick Tomato under Free-Obstacle

2012 ◽  
Vol 229-231 ◽  
pp. 2225-2228
Author(s):  
Jian Jun Yin ◽  
Chun Xie ◽  
Chuan Yu Wu ◽  
S.Mittal Gauri ◽  
Simon X. Yang
Keyword(s):  
Real Time ◽  
Inverse Kinematics ◽  
Energy Optimization ◽  
Constant Speed ◽  
Motion Path ◽  
Robot Arm ◽  
Joint Angles ◽  
Object Point ◽  
Straight Path

To improve the efficiency of picking the fruit, a kind of quick motion path plan method for fruit-picking robot under free-obstacle was proposed in this paper. Firstly, the method obtained a series of points along straight path at equal internal, and the gripper center was designed to pass thorough these points. Inverse kinematics formulas of the robot arm were used to solve joint angles of the robot arm when the gripper center will pass thorough each point. To make the robot arm guide the gripper to reach quickly the object point, the joint angles were optimized to determinate according to the principle of energy optimization. The test of picking tomato showed that the method can both reproduce the motion of the gripper along linear points at constant speed and keep the shortest motion path, which are benefit to grip the fruit steadily. The method has a low amount of calculation, better real-time and may provide a reference for joint robot to pick the fruit quickly.

scholarly journals Whole-Body Joint Angle Estimation for Real-Time Humanoid Robot Imitation Based on Gaussian Process Dynamical Model and Particle Filter

2019 ◽  
Vol 10 (1) ◽  
pp. 5
Author(s):  
Jian Mi ◽  
Yasutake Takahashi
Keyword(s):  
Particle Filter ◽  
Real Time ◽  
Humanoid Robot ◽  
Joint Angle ◽  
Computational Cost ◽  
High Dimensional ◽  
Motion Model ◽  
Joint Angles ◽  
Compact State ◽  
Low Computational Cost

Real-time imitation enables a humanoid robot to mirror the behavior of humans, being important for applications of human–robot interaction. For imitation, the corresponding joint angles of the humanoid robot should be estimated. Generally, a humanoid robot comprises dozens of joints that construct a high-dimensional exploration space for estimating the joint angles. Although a particle filter can estimate the robot state and provides a solution for estimating joint angles, the computational cost becomes prohibitive given the high dimension of the exploration space. Furthermore, a particle filter can only estimate the joint angles accurately using a motion model. To realize accurate joint angle estimation at low computational cost, Gaussian process dynamical models (GPDMs) can be adopted. Specifically, a compact state space can be constructed through the GPDM learning of high-dimensional time-series motion data to obtain a suitable motion model. We propose a GPDM-based particle filter using a compact state space from the learned motion models to realize efficient estimation of joint angles for robot imitation. Simulations and real experiments demonstrate that the proposed method efficiently estimates humanoid robot joint angles at low computational cost, enabling real-time imitation.

Singularity-Robust Inverse Kinematics Using Lagrange Multiplier for Redundant Manipulators

2008 ◽  
Vol 130 (5) ◽  
Author(s):  
Youngjin Choi
Keyword(s):  
Lagrange Multiplier ◽  
Inverse Kinematics ◽  
Equality Constraint ◽  
Primary Task ◽  
Redundant Manipulator ◽  
Natural Choice ◽  
Inverse Kinematics Problem ◽  
Ill Conditioning ◽  
Singular Configuration ◽  
Dual Arm

In this paper, a singularity-robust inverse kinematics is newly suggested by using a Lagrange multiplier for redundant manipulator systems. Two tasks are considered with priority orders under the assumption that a primary task has no singularity. First, an inverse kinematics problem is formulated to be an optimization one subject to an equality constraint, in other words, to be a minimization problem of secondary task error subject to an equality constraint for primary task execution. Second, in the procedure of minimization for a given objective function, a new inverse kinematics algorithm is derived. Third, since nonzero Lagrange multiplier values appear in the neighborhood of a singular configuration of a robotic manipulator, we choose them as a natural choice of the dampening factor to alleviate the ill-conditioning of matrix inversion, ultimately for singularity-robust inverse kinematics. Finally, the effectiveness of the suggested singularity-robust inverse kinematics is shown through a numerical simulation about deburring and conveyance tasks of a dual arm manipulator system.

A numerically stable algorithm for analytic inverse kinematics of 7-DoF S-R-S manipulators with joint limit avoidance

2021 ◽  
pp. 1-15
Author(s):  
Junchen Wang ◽  
Chunheng Lu ◽  
Yinghao Zhang ◽  
Zhen Sun ◽  
Yu Shen
Keyword(s):  
Inverse Kinematics ◽  
Joint Angle ◽  
State Of The Art ◽  
Joint Angles ◽  
Stable Algorithm ◽  
Angle Space ◽  
Joint Limits ◽  
Self Motion ◽  
Configuration Control ◽  
Joint Limit

Abstract This paper presents a numerically stable algorithm for analytic inverse kinematics of 7-DoF S-R-S manipulators with joint limit avoidance. The arm angle is used to represent the self-motion manifold within a global arm configuration. The joint limits are analytically mapped to the arm angle space for joint limit avoidance. To profile the relation between the joint angle and arm angle, it is critical to characterize the singular arm angle for each joint. In the-state-of-the art methods, the existence of the singular arm angle is triggered by comparing a discriminant with zero given a threshold. We will show this leads to numerical issues since the threshold is inconsistent among different target poses, leading to incorrect range of the arm angle. These issues are overcome by associating indeterminate joint angles of tangent joints with angles of 0 or pi of cosine joints, rather than using an independent threshold for each joint. The closed-form algorithm in C++ code to perform numerically stable inverse kinematics of 7-DoF S-R-S manipulators with global arm configuration control and joint limit avoidance is also given.

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