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Collaborative Robotics and Collision Avoidance in Human-Robot Shared Workspaces.
Rel. Stefano Mauro, Matteo Melchiorre, Laura Salamina. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Meccanica (Mechanical Engineering), 2025
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Abstract
Collaborative robotics blends the precision of industrial manipulators with human dexterity in a shared workspace. Safety dictates motion: power-and-force limiting and, especially, speed-and-separation monitoring (SSM) regulate robot behavior to maintain provable human–robot clearances and have shaped recent human–robot collaboration (HRC) practice. Turning these requirements into control means expressing separation and interaction constraints as bounds on position, velocity, and interaction effort, then generating trajectories and joint commands that remain feasible under sensing noise and kinematic limits. For redundant manipulators, task-priority control with null-space projection executes the primary end-effector objective while simultaneously shaping posture, respecting joint limits, and accommodating collision-avoidance biases drawn from perception.
Robustness near kinematic singularities is achieved with damped least-squares (DLS) solved via singular-value decomposition (SVD), which attenuates ill-conditioned directions and regularizes the inverse kinematics in real time
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