| Summary: | This article proposes a collision detection algorithm without external sensors that can detect potential collisions in man–robot interaction. The algorithm is based on a modified first-order momentum deviation observer that also takes friction into account. The collision detection algorithm uses joint angles, angular velocities, and torques during the detection process, without any need to consider angular acceleration. The algorithm also uses an accurate friction model that is based on a Stribeck model with second-order Fourier series compensation. The friction model is applied in advance so that compensation can be made in real time during collision detection. Identification data are filtered through a first-order low-pass filter to reduce high-frequency noise. In order to verify the algorithm, a simulation and experiment were carried out using a collaborative robot experimental platform. The results confirmed that collisions can be detected by setting appropriate threshold values. Different possible responses can be implemented according to different response strategies, with the ultimate arbiter being that collision forces are kept strictly within ordinary human tolerances. This makes sure that safety can be preserved in man–robot interaction processes.
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