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.

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.

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 Sensor-based skeleton modeling and MVEEs approach of the redundant manipulator for reaction motion

2022 ◽  
Vol 14 (1) ◽  
pp. 168781402210742
Author(s):  
Lan Ye ◽  
Genliang Xiong ◽  
Hua Zhang ◽  
Cheng Zeng
Keyword(s):  
Obstacle Avoidance ◽  
Reaction Force ◽  
Redundant Manipulator ◽  
Joint Angles ◽  
Damping Term ◽  
Multiple Control ◽  
Multiple Points ◽  
Working Space ◽  
Dynamic Obstacle Avoidance ◽  
Dynamic Obstacle

With the wide application of redundant manipulators, sharing a working space with humans and dealing with uncertainty seems an inevitable problem, especially in the dynamic and unstructured domain. How to deal with obstacle avoidance is of particular importance that robots and humans/environments are safe interactions to fulfill the complex cooperating tasks. This paper aimed at solving the problem of multiple points avoidance for the reaction motion based on the skeleton algorithm in unstructured and dynamic environments. A method named “sensor-based skeleton modeling and MVEEs approach of the redundant manipulator for the reaction motion” is proposed. The extraction of skeleton information from image is obtained to calculate the distances of the multiple control points and establish the repulsion in this method. Afterward, the force Jacobian related to the priority weighting factors is calculated and then a reaction force with damping term is established, which is corresponding nominal torque commands. For the redundant manipulator, the joint angles are obtained through torque iteration instead of inverse kinematics to reduce calculation cost. Finally, the method was tested by a 7-DOF manipulator in the ROS framework. The obtained results indicate that the method in this method can realize dynamic obstacle avoidance and time cost reduction.

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.

scholarly journals Genome-Wide Association Studies Based on Equine Joint Angle Measurements Reveal New QTL Affecting the Conformation of Horses

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 370 ◽  
Author(s):  
Annik Imogen Gmel ◽  
Thomas Druml ◽  
Rudolf von Niederhäusern ◽  
Tosso Leeb ◽  
Markus Neuditschko
Keyword(s):  
Joint Angle ◽  
Association Studies ◽  
Genome Wide Association ◽  
Cranial Morphology ◽  
Genome Wide Association Studies ◽  
Joint Angles ◽  
Mineral Density ◽  
Mixed Effect ◽  
Stifle Joint ◽  
Genome Wide

The evaluation of conformation traits is an important part of selection for breeding stallions and mares. Some of these judged conformation traits involve joint angles that are associated with performance, health, and longevity. To improve our understanding of the genetic background of joint angles in horses, we have objectively measured the angles of the poll, elbow, carpal, fetlock (front and hind), hip, stifle, and hock joints based on one photograph of each of the 300 Franches-Montagnes (FM) and 224 Lipizzan (LIP) horses. After quality control, genome-wide association studies (GWASs) for these traits were performed on 495 horses, using 374,070 genome-wide single nucleotide polymorphisms (SNPs) in a mixed-effect model. We identified two significant quantitative trait loci (QTL) for the poll angle on ECA28 (p = 1.36 × 10−7), 50 kb downstream of the ALX1 gene, involved in cranial morphology, and for the elbow joint on ECA29 (p = 1.69 × 10−7), 49 kb downstream of the RSU1 gene, and 75 kb upstream of the PTER gene. Both genes are associated with bone mineral density in humans. Furthermore, we identified other suggestive QTL associated with the stifle joint on ECA8 (p = 3.10 × 10−7); the poll on ECA1 (p = 6.83 × 10−7); the fetlock joint of the hind limb on ECA27 (p = 5.42 × 10−7); and the carpal joint angle on ECA3 (p = 6.24 × 10−7), ECA4 (p = 6.07 × 10−7), and ECA7 (p = 8.83 × 10−7). The application of angular measurements in genetic studies may increase our understanding of the underlying genetic effects of important traits in equine breeding.

scholarly journals Experimental and Numerical Study of Fracture Behavior of Rock-Like Material Specimens with Single Pre-Set Joint under Dynamic Loading

Materials ◽  
2021 ◽  
Vol 14 (10) ◽  
pp. 2690
Author(s):  
Bo Pan ◽  
Xuguang Wang ◽  
Zhenyang Xu ◽  
Lianjun Guo ◽  
Xuesong Wang
Keyword(s):  
Crack Initiation ◽  
Crack Propagation ◽  
Joint Angle ◽  
Simulation Software ◽  
Dissipated Energy ◽  
Energy Structure ◽  
Joint Angles ◽  
Crack Penetration ◽  
Before And After ◽  
The Impact

The Split Hopkinson Pressure Bar (SHPB) is an apparatus for testing the dynamic stress-strain response of the cement mortar specimen with pre-set joints at different angles to explore the influence of joint attitudes of underground rock engineering on the failure characteristics of rock mass structure. The nuclear magnetic resonance (NMR) has also been used to measure the pore distribution and internal cracks of the specimen before and after the testing. In combination with numerical analysis, the paper systematically discusses the influence of joint angles on the failure mode of rock-like materials from three aspects of energy dissipation, microscopic damage, and stress field characteristics. The result indicates that the impact energy structure of the SHPB is greatly affected by the pre-set joint angle of the specimen. With the joint angle increasing, the proportion of reflected energy moves in fluctuation, while the ratio of transmitted energy to dissipated energy varies from one to the other. NMR analysis reveals the structural variation of the pores in those cement specimens before and after the impact. Crack propagation direction is correlated with pre-set joint angles of the specimens. With the increase of the pre-set joint angles, the crack initiation angle decreases gradually. When the joint angles are around 30°–75°, the specimens develop obvious cracks. The crushing process of the specimens is simulated by LS-DYNA software. It is concluded that the stresses at the crack initiation time are concentrated between 20 and 40 MPa. The instantaneous stress curve first increases and then decreases with crack propagation, peaking at different times under various joint angles; but most of them occur when the crack penetration ratio reaches 80–90%. With the increment of joint angles in specimens through the simulation software, the changing trend of peak stress is consistent with the test results.

scholarly journals Collision-free path planning for welding manipulator via hybrid algorithm of deep reinforcement learning and inverse kinematics

2021 ◽  
Author(s):  
Jie Zhong ◽  
Tao Wang ◽  
Lianglun Cheng
Keyword(s):  
Reinforcement Learning ◽  
Path Planning ◽  
Free Path ◽  
Inverse Kinematics ◽  
Multiple Dimensions ◽  
Continuous State ◽  
Planning Algorithm ◽  
Convergence Performance ◽  
Path Planner ◽  
Action Spaces

AbstractIn actual welding scenarios, an effective path planner is needed to find a collision-free path in the configuration space for the welding manipulator with obstacles around. However, as a state-of-the-art method, the sampling-based planner only satisfies the probability completeness and its computational complexity is sensitive with state dimension. In this paper, we propose a path planner for welding manipulators based on deep reinforcement learning for solving path planning problems in high-dimensional continuous state and action spaces. Compared with the sampling-based method, it is more robust and is less sensitive with state dimension. In detail, to improve the learning efficiency, we introduce the inverse kinematics module to provide prior knowledge while a gain module is also designed to avoid the local optimal policy, we integrate them into the training algorithm. To evaluate our proposed planning algorithm in multiple dimensions, we conducted multiple sets of path planning experiments for welding manipulators. The results show that our method not only improves the convergence performance but also is superior in terms of optimality and robustness of planning compared with most other planning algorithms.

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