A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Reinforcement Learning Human Inverse Kinematics of an Upper Limb Exoskeleton Robot
This paper presents a Reinforcement Learning (RL)-based swivel angle estimation for an upper-limb 7-DoF exoskeleton robot. Choosing the best swivel angle in the rehabilitation process helps in ensuring the safety and the comfortability of the patient's upper-extremity movement. Also, fixing the swivel angle will result in having one unique IK solution. The RL agent is trained to estimate the swivel angle that minimizes the discomfort index of the patient's upper limb. After training the agent, it is used to simulate a workspace trajectory to validate the IK solution with the fixed swivel angle value. Simulation results are showing the feasibility and effectiveness of using RL in solving the IK for 7-DoF exoskeleton robots.
Reinforcement Learning Human Inverse Kinematics of an Upper Limb Exoskeleton Robot
This paper presents a Reinforcement Learning (RL)-based swivel angle estimation for an upper-limb 7-DoF exoskeleton robot. Choosing the best swivel angle in the rehabilitation process helps in ensuring the safety and the comfortability of the patient's upper-extremity movement. Also, fixing the swivel angle will result in having one unique IK solution. The RL agent is trained to estimate the swivel angle that minimizes the discomfort index of the patient's upper limb. After training the agent, it is used to simulate a workspace trajectory to validate the IK solution with the fixed swivel angle value. Simulation results are showing the feasibility and effectiveness of using RL in solving the IK for 7-DoF exoskeleton robots.
Reinforcement Learning Human Inverse Kinematics of an Upper Limb Exoskeleton Robot
Abdallah, Mahmoud (author) / Saad, Maarouf (author) / Fareh, Raouf (author) / Kali, Yassine (author) / Bettayeb, Maamar (author)
2023-02-20
1746046 byte
Conference paper
Electronic Resource
English
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