{'fraction_non_alphanumeric': 0.01872871736662883, 'fraction_numerical': 0.0005675368898978433, 'mean_word_length': 5.229681978798586, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Control of a power assist robot for lifting objects based on human operator's perception of object weight

An object lifted with a power assist robot is always perceived lighter than its actual weight. But, the human operator cannot differentiate between the power assisted weight and the actual weight and eventually applies load force (vertical lifting force) according to the actual weight of the object. This faulty force programming (excessive load force) gives faulty motions to the power assist robot and jeopardizes its operability, maneuverability, ease of use, naturalness, human-friendliness, safety etc. In this paper we assume that these problems still exist with the power assist robots because human's weight perception is not included in the design and control of the conventional power assist robots .We hypothesize that human's perception of weight due to inertial force may be different from the perceived weight due to gravitational force for lifting object with a power assist robot. Based on this hypothesis, we designed a 1 DOF power assist robot and established a psychophysical relationship between the actual weights and the power assisted weights for the objects lifted with the robot. We also determined the excess of the load forces that humans applied. Then, we modified the control system of the power assist robot based on the psychophysical relationship and the load force characteristics. The modification of the control system reduced the peak load forces applied by humans and thus enhanced maneuverability, naturalness, ease of use, stability, safety etc. of the robot system significantly. Finally, we proposed using the findings to design human-friendly power assist robots for carrying heavy objects in various industries.