In this thesis, solutions to two of the problems encountered in the design and control of human-friendly robots are investigated. The first problem is severe human injuries can occur when an accidental human-manipulator impact happens. A theoretical and experimental study on using foam coverings to reduce the severity of a human-manipulator impact and enhance human safety is presented. An improved human-manipulator impact model that incorporates the manipulator dynamics, foam covering dynamics and the coupling between the human head and torso is introduced. A method for approximating the configuration-dependent dynamics of robotics manipulators with the dynamics of a single DOF manipulator is proposed. With this model, the design parameters that significantly influence the human head acceleration are investigated. A model-based foam covering design procedure to properly select parameters of foam coverings in accordance with safety criteria and the foam thickness constraint is then proposed. The impact model and the foam covering design procedure are validated experimentally with two manipulators. The maximum error between the predicted and experimental head acceleration was less than 9%. The maximum error between the predicted and experimental foam compressed depth was less than 12%.

The second problem is mobile robot navigation in the presence of humans and other motion-unpredictable obstacles. A novel navigation algorithm, based on the virtual force field (VFF) method, is proposed as a solution. It features improved functions for the repulsive and detour virtual forces, and a new stabilizing virtual force. Methods to calculate sizes of the active and critical regions for different obstacles are developed. Stability of the new VFF is proven using a novel piecewise Lyapunov function and Lyapunov's second method. Based on simulations for different obstacle configurations, the new VFF-based algorithm successfully produces collision-free paths while five well known navigation algorithms incurred collisions in one of the configurations. With the new VFF-based navigation algorithm, simulations and experiments are successfully performed with a holonomic robot and a nonholonomic robot for several configurations, including multiple moving obstacles.