Exoskeleton for Operator's Motion Сapture With Master-Slave Control

Abstract

The study is devoted to the development of the structure of the upper-limb exoskeleton for operator's motion capture with master-slave control. The objective of the study is to develop design solutions in the field of registration of the current position of the operator's hand parts during the technological operations of the control commands formation for their accurate reproduction by the movements of the anthropomorphic manipulator links in real time. For the developed structure of the upper-limb exoskeleton, the division of the product scheme is described, the rationale for the design, the layout of kinematic pairs equipped with angular rotation sensors, and the design of the lever system that duplicates the operator's hand with its metric parameters is given. To check the efficiency of the exoskeleton design, a simulation program was used. The accuracy of the rotation angle of the exoskeleton elbow joint in the simulation model does not exceed 3.4%, shoulder joint-5.2%. The presented structure of the exoskeleton will allow to register the current positions of the operator's hand parts when performing technological operations and to form control commands for their accurate reproduction by the links of the manipulator.

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

“…The purpose of the calculation is to determine the Cartesian coordinates 𝑥 ℎ ′ , 𝑦 ℎ ′ , 𝑧 ℎ ′ and Euler angles𝛼 ′ , 𝛽 ′ , 𝛾′of the operator's virtual brush relative to the operator's center of vision (Fig. 3), as well as rotation angles𝜽 ′ in the joints of the fingers of the operator's virtual hand [16][17][18][19].  Eulerangles 𝛼, 𝛽, 𝛾of the operator's hand relative to the coordinate system associated with the operator;…”

Variable Admittance Control of a Hand Exoskeleton for Virtual Reality-Based Rehabilitation Tasks

“…Exoskeletons are a promising technology with a vast range of applications from the military to the industrial fields, from healthcare to injury prevention in physically stressful jobs. Besides, such devices are not only used to support the human body but can be exploited to drive an external robot in a primary-replicas fashion (Huang et al, 2018 ; Petrenko et al, 2019 ) or in imitation learning applications (Huang et al, 2019 ; Hua et al, 2021 ). In the last decades, an increasing number of exoskeletons have been designed for patients affected by motor dysfunctions or disabilities and applied in rehabilitation therapies, guided training, or assistance in everyday actions (Molteni et al, 2018 ; Shi et al, 2019 ; du Plessis et al, 2021 ).…”

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

“…Mobile manipulation robotic complexes belong to the category of service robots that can be used in the domestic sphere, when performing emergency rescue operations and research missions. Examples of the use of service robots are harvesting in agriculture, delivering food and reception of orders at catering establishments, caring for sick and disabled people, cleaning rooms, performing emergency and rescue operations (to monitor the emergency zone and eliminate the consequences of emergency situations), moon exploration and Mars, demining, military operations (fire support, delivery of supplies and medicines, transportation of the wounded, reconnaissance), diagnostics and maintenance of pipelines [2][3][4].…”