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Design and Implementation of a Cable Robot for Rehabilitation

Latifi, Mohammad
A Master of Science thesis in Mechatronics Engineering by Mohammad Latifi entitled, “Design and Implementation of a Cable Robot for Rehabilitation”, submitted in December 2022. Thesis advisor is Dr. Lotfi Romdhane and thesis co-advisor is Dr. Mohammad Jaradat. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).
Due to the precision and repeatability that current robotic system offer; many researchers and innovators have proposed solution for biomedical needs and applications. Classical robots can offer great precision and offer a high payload-to-weight mechanism to handle different biomedical tasks. Nonetheless, the classical robots might act poorly where the adaptability and flexibility of the system is challenged. One way of tackling these issues is to use Cable-Driven Parallel Robot (CDPR) to address all the issues raised by the performance measures mentioned earlier. Due to the flexible links used in CDPR, the control of the system becomes a challenging problem and many researchers have developed different solutions to overcome many modeling problems, including unilateral condition, where links of the robot will be actuated only upon pulling an object. Under the studies that have been done for this thesis work, a CDPR robot has been prototyped with a control joint scheme, where the motion of the robot has been set through Geometric Inverse Kinematic (GIK), and the motors are controlled through PID control that receives feedback from each motor encoder. Later in this study, the performance of the system has been studied under 11 different cases under different trajectory conditions. It has been shown that the best steady state is achieved when the robot has the smallest acceleration or deceleration among the via points, which gives the Integral Square Error (ISE) value of 25.3. The transient response, however, has the best performance when a lower number of via points has been selected for a given path, which gives the Integrated Time Absolute Error (ITAE) of 706.2. The system performs the trajectory planning in absence of high-level control or encountering errors introduced by model measurement inaccuracies.
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