Integração de visão computacional e robótica clássica para manipulação assistiva

Abstract

This work proposes an approach that integrates computer vision techniques with classical robotics methods, aiming to improve the quality of life for people with disabilities and the elderly by providing autonomy in dressing tasks. Using a Kinova Gen3 robotic manipulator with seven degrees of freedom, the study implements color segmentation, edge detection, and Hough transform algorithms to identify the patient’s arm position, guide the robot

approach, and generate safe trajectories for garment manipulation. In a simulated environ- ment using CoppeliaSim and an RGB-D sensor, different arm positioning configurations

were evaluated, demonstrating the system feasibility in offering personalized and secure assistance for individuals with reduced mobility. The integration of computer vision methods with trajectory planning significantly contributes to increasing user autonomy, presenting a promising alternative for assistive robotics implementation.