Precision Control of Prosthetic Hand: Modeling Analytical, Simulation in Real-World Implementation
Session Number
1
Advisor(s)
Dr. Ashwin Mohan, PhD, SYNAPSE Lab, IMSA
Location
A150
Discipline
Engineering
Start Date
15-4-2026 10:15 AM
End Date
15-4-2026 11:00 AM
Abstract
In robotic surgery, precision continues to be one of the primary challenges due to external mechanical variables such as viscous friction, Coulomb friction, inertia, and backlash deadbands. Current mathematical models of prosthetic systems do not consider these variables. The aim of this study is to achieve one-to-one correspondence between analytical, simulated and real-world hardware implementation, and to achieve precision in the robotic arm’s movement. An analytical model of a tabletop 6 Degree of Freedom (DOF) robotic arm was computed using forward and inverse kinematics. Forward kinematics take joint angles and link lengths into account to predict trajectory, and inverse kinematics was used to determine the link lengths and joint angles form the end effector positions. Data from the inverse kinematics end effector was fed into a MATLAB simulation along with the Damped Least Squares (DLS) technique. This resolved the movement of the system in simulation and helped in visualizing the system. Finally, a 6 axis robot was interfaced with MATLAB to test and validate simulation behavior, ensuring the software interacts correctly with the physical hardware. Results demonstrated positional accuracy between simulated and hardware outputs, indicating that real-world mechanical variables in kinematic models improve predictability and precision of prosthetic control systems.
Precision Control of Prosthetic Hand: Modeling Analytical, Simulation in Real-World Implementation
A150
In robotic surgery, precision continues to be one of the primary challenges due to external mechanical variables such as viscous friction, Coulomb friction, inertia, and backlash deadbands. Current mathematical models of prosthetic systems do not consider these variables. The aim of this study is to achieve one-to-one correspondence between analytical, simulated and real-world hardware implementation, and to achieve precision in the robotic arm’s movement. An analytical model of a tabletop 6 Degree of Freedom (DOF) robotic arm was computed using forward and inverse kinematics. Forward kinematics take joint angles and link lengths into account to predict trajectory, and inverse kinematics was used to determine the link lengths and joint angles form the end effector positions. Data from the inverse kinematics end effector was fed into a MATLAB simulation along with the Damped Least Squares (DLS) technique. This resolved the movement of the system in simulation and helped in visualizing the system. Finally, a 6 axis robot was interfaced with MATLAB to test and validate simulation behavior, ensuring the software interacts correctly with the physical hardware. Results demonstrated positional accuracy between simulated and hardware outputs, indicating that real-world mechanical variables in kinematic models improve predictability and precision of prosthetic control systems.