Application of Linear Algebra Approaches for Predicting Self-Collisions of Dual-Arm Multi-Link Robot

Kramar, Vadim; Kabanov, Aleksey; Alchakov, Vasiliy

doi:10.18178/ijmerr.9.11.1521-1525

Cited by 6 publications

(5 citation statements)

References 14 publications

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“…The most modern collision detection methods are based on analytical approaches [19][20][21][22][23][24][25][26]. In [7], an ANN solution on the basis of the "Contextual" ANN to predicting the self-collision of multilink manipulators is proposed.…”

Section: Introductionmentioning

confidence: 99%

Neural Network Method of Controlling Self-Collisions of Multilink Manipulators Based on the Solution of the Classification Problem

Kramar,

Kabanov

et al. 2023

Applied Sciences

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The problem of self-collisions of manipulators with several links installed on a robot can arise when they work together in one zone. To prevent self-collisions, it is necessary to develop methods for their detection and their subsequent inclusion in control algorithms. This paper proposes an approach for determining the occurrence of self-collisions of manipulators using the Artificial Neural Networks approach. In contrast to the regression problem, this article proposes a classification approach. The effectiveness of the proposed approach was tested on robots with multilink manipulators “Ichtiandr” and SAR-401 and their simulators. Self-collision detection using the proposed method is much faster than using the traditional approach of solving the inverse kinematics problem without loss of accuracy. The problem was solved by constructing various Artificial Neural Networks and then checking the accuracy of the solution. A comparative analysis of Artificial Neural Networks was carried out and as a result, the Artificial Neural Networks approach showing the best accuracy was selected. The problem was solved for a robot with two manipulators. The resulting solution can be extended to a larger number of manipulators installed on the robot.

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Section: Introductionmentioning

confidence: 99%

Neural Network Method of Controlling Self-Collisions of Multilink Manipulators Based on the Solution of the Classification Problem

Kramar,

Kabanov

et al. 2023

Applied Sciences

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“…In particular, for robots with several manipulators, there is a danger that manipulators will collide with each other. Such collisions are called self-collisions [7][8][9][10][11]. For robots with a copy-type control, the self-collisions control problem falls on the operator.…”

Section: Introductionmentioning

confidence: 99%

“…Vadim Kramar, Self-Collision Avoidance Control of Dual-Arm Multi-Link Robot Using Neural Network Approach and the search of the coordinates and their combinations at which these critical positions arise [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24]. In [7], the authors presented a solution of the problem of two manipulators motion control using a constraint-based programming approach, which was used to generate online motion plans.…”

Section: Introductionmentioning

confidence: 99%

“…Another approach is based on the search for restrictions on control signals that exclude the movement of manipulators with the intersection of the trajectories of all the parts of the manipulators. In [8,9,25], the authors proposed a simple approach based on linear algebra methods for self-collisions control of multilink manipulators. In [14], to detect the manipulators collisions and represent them in a twodimensional coordinate system, the so-called collision map was proposed as a collision zone.…”

Section: Introductionmentioning

confidence: 99%

“…The proposed design is based on the use of the special choice of the structure of the input dataset and experimental choice of the structure of the neural network. The approach proposed in the article made it possible to reduce the computation time by approximately 10 times compared to the application of the computational approach to the analysis of the self-collision [8,9] while maintaining the specified accuracy. By reducing the computation time, the approach proposed in the article becomes an effective tool for developing a control program with an online mode for detecting and avoiding selfcollisions of multi-link manipulators.…”

Section: Introductionmentioning

confidence: 99%

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Self-Collision Avoidance Control of Dual-Arm Multi-Link Robot Using Neural Network Approach

Kramar

Kabanov

2022

Journal of Robotics and Control

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The problem of mutual collisions of manipulators of a dual-arm multi-link robot (so-called self-collisions) arises during the performance of a cooperative technological operation. Self-collisions can lead to non-fulfillment of the technological operation or even to the failure of the manipulators. In this regard, it is necessary to develop a method for online detection and avoidance of self-collisions of manipulators. The article presents a method for detecting and avoiding self-collisions of multi-link manipulators using an artificial neural network by the example of the dual-arm robot SAR-401. A comparative analysis is carried out and the architecture of an artificial neural network for self-collisions avoidance control of dual-arm robot manipulators is proposed. The novelty of the proposed approach lies in the fact that it is an alternative to the generally accepted methods of detecting self-collisions based on the numerical solution of inverse kinematics problems for manipulators in the form of nonlinear optimization problems. Experimental results performed based on MATLAB model, the simulator of the robot SAR-401 and on the real robot itself confirmed the applicability and effectiveness of the proposed approach. It is shown that the detection of possible self-collisions using the proposed method based on an artificial neural network is performed approximately 10 times faster than approaches based on the numerical solution of the inverse kinematics problem while maintaining the specified accuracy.

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A Safe Shared-Control Framework for Dual-Arm Collaborative Telemanipulation

Ge,

Zhao,

Chen

et al. 2024

2023 8th International Conference on Control, Robotics and Cybernetics (CRC)

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Application of Linear Algebra Approaches for Predicting Self-Collisions of Dual-Arm Multi-Link Robot

Cited by 6 publications

References 14 publications

Neural Network Method of Controlling Self-Collisions of Multilink Manipulators Based on the Solution of the Classification Problem

Neural Network Method of Controlling Self-Collisions of Multilink Manipulators Based on the Solution of the Classification Problem

Self-Collision Avoidance Control of Dual-Arm Multi-Link Robot Using Neural Network Approach

A Safe Shared-Control Framework for Dual-Arm Collaborative Telemanipulation

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