Analysis of the Effectiveness Path Planning Methods and Algorithm for the Anthropomorphic Robot Manipulator

Петренко, В. И.; Тебуева, Фариза; Antonov, V. O.; Gurchinsky, M. M.; Pavlov, A. S.; Ryabtsev, Sergey; Shutova, Yuliya

doi:10.1109/sibcon.2019.8729657

Cited by 8 publications

(5 citation statements)

References 7 publications

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“…Where zF is derived from the difference between the friction of SMO given in ( 7) and the friction model given in (2). By taking derivative with respect to time of ( 21), We'll get ( 22)…”

Section: A Stability With Lyapunov Functionmentioning

confidence: 99%

“…With the rapid advancement of automation in the industrial era, robotic manipulators are becoming highly significant in medical, renewable energy, textile and agriculture etc., applications [1]. The manipulator tasks must be controlled safely, efficiently and consistently to achieve high production or efficient exploration [2]. As a result, improved robotic manipulators controllers are required to deliver high accuracy under various diverse situations affected by the operating environment, including external noise, measurement mistakes, or unknown uncertain components [3].…”

Section: Introductionmentioning

confidence: 99%

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Terminal Sliding Mode Control of an Anthropomorphic Manipulator with Friction Based Observer

Ali

Mehmood

Iqbal

2021

2021 International Conference on Robotics and Automation in Industry (ICRAI)

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The role of modern control techniques has been instrumental in today's robotic applications because of their increasing requirements for reliability, accuracy, productivity and repeatability. Robotic manipulators are highly non-linear systems with coupled dynamics and thus are vulnerable to a lot of disturbances such as unknown payloads, dynamics that the model and joint friction do not predict. To achieve superior performance and reliability in the presence of friction, this research proposes a robust control algorithm for a five-degree-of-freedom (DoF) robotic manipulator. The dynamic LuGre friction model is used to develop the robot's dynamic model. A sliding mode observer (SMO) is proposed for the estimation of the internal friction state of the LuGre model. The friction and load torque are based on an estimated state to compensate for unidentified friction. A Lyapunov candidate function is used to check the stability of the controller with the SMO. The proposed control methodology has been designed and implemented in MATLAB/Simulink environment to illustrate the tracking of various trajectories. This study's outcomes proved that the proposed control law with model-based friction compensation is effective and efficient.

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“…Where zF is derived from the difference between the friction of SMO given in ( 7) and the friction model given in (2). By taking derivative with respect to time of ( 21), We'll get ( 22)…”

Section: A Stability With Lyapunov Functionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Terminal Sliding Mode Control of an Anthropomorphic Manipulator with Friction Based Observer

Ali

Mehmood

Iqbal

2021

2021 International Conference on Robotics and Automation in Industry (ICRAI)

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“…However, issues such as the search for tomatoes with the help of technical vision, the capture of fruits and further manipulation with them are not considered. Methods for performing these tasks are proposed in articles [18][19][20][21][22][23].…”

Section: A Limitationsmentioning

confidence: 99%

A Robotic Complex Control Method Based on Deep Reinforcement Learning of Recurrent Neural Networks for Automatic Harvesting of Greenhouse Crops

Петренко¹,

Тебуева²,

Antonov³

et al. 2020

Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)

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The modern development of technology determines the feasibility of the transition in agriculture from manual labor to automatic production. One of the promising areas is the automation of growing vegetable crops in greenhouse complexes. Necessary factors for intensive plant growth and unfavorable for human health, such as high temperature and humidity, as well as an atmosphere saturated with chemicals, make the task of robotizing agricultural operations urgent in this area. The method for controlling a robotic complex for automatic fruit collection in greenhouse complexes is proposed. Work in greenhouse complexes is characterized as non-deterministic and with partial observability of the environment; therefore, the deep recurrent neural network DRQN was used as the basis for the method of controlling the robotic complex. Deep learning with reinforcement was used for optimizing its weights. The presented simulation results demonstrate the efficiency of the proposed method and the need for its further development.

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“…Based on the existing methods for solving kinematics problems (graph-analytical methods, genetic algorithms, machine learning, fuzzy logic, spline interpolation), it is proposed to use the Denavit-Hartenberg representation and the approach to calculating the rotation angles of the operator's hand described in [13][14][15][16].…”

Section: Analytical Review Of Current Developments Of Haptic Gloves A...mentioning

confidence: 99%

Method of Planning the Trajectory of an Anthropomorphic Manipulator With a Copying Control With Haptic Gloves

Петренко¹,

Antonov²,

Тебуева³

et al. 2020

Proceedings of the 8th Scientific Conference on Information Technologies for Intelligent Decision Making Support (ITIDS 2020)

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The article presents the development of a method for planning the trajectory of motion of the joints of an anthropomorphic manipulator in virtual reality with copy control with haptic gloves based on the method of calculating the position of the operator's hands. The article discusses the existing development of haptic gloves, analyzes the scientific publications on this topic, which showed a variety of technical solutions. Two methods for the implementation of haptic gloves are indicated, for which the calculation of the path of movement of the robot arm is performed. The method of planning the trajectory of motion of the joints of the anthropomorphic manipulator with copy control using haptic gloves is based on the Denavit-Hartenberg representation and the developed method and calculating the position of the operator's hands in virtual reality.

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Analysis of the Effectiveness Path Planning Methods and Algorithm for the Anthropomorphic Robot Manipulator

Cited by 8 publications

References 7 publications

Terminal Sliding Mode Control of an Anthropomorphic Manipulator with Friction Based Observer

Terminal Sliding Mode Control of an Anthropomorphic Manipulator with Friction Based Observer

A Robotic Complex Control Method Based on Deep Reinforcement Learning of Recurrent Neural Networks for Automatic Harvesting of Greenhouse Crops

Method of Planning the Trajectory of an Anthropomorphic Manipulator With a Copying Control With Haptic Gloves

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