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BACKGROUND: Nowadays, workplace violence is found to be a mental health hazard and considered a crucial topic. The collaboration between robots and humans is increasing with the growth of Industry 4.0. Therefore, the first problem that must be solved is human-machine security. Ensuring the safety of human beings is one of the main aspects of human-robotic interaction. This is not just about preventing collisions within a shared space among human beings and robots; it includes all possible means of harm for an individual, from physical contact to unpleasant or dangerous psychological effects. OBJECTIVE: In this paper, Non-linear Adaptive Heuristic Mathematical Model (NAHMM) has been proposed for the prevention of workplace violence using security Human-Robot Collaboration (HRC). Human-Robot Collaboration (HRC) is an area of research with a wide range of up-demands, future scenarios, and potential economic influence. HRC is an interdisciplinary field of research that encompasses cognitive sciences, classical robotics, and psychology. RESULTS: The robot can thus make the optimal decision between actions that expose its capabilities to the human being and take the best steps given the knowledge that is currently available to the human being. Further, the ideal policy can be measured carefully under certain observability assumptions. CONCLUSION: The system is shown on a collaborative robot and is compared to a state of the art security system. The device is experimentally demonstrated. The new system is being evaluated qualitatively and quantitatively. [ABSTRACT FROM AUTHOR]

A modified fuzzy relational modeling structure is presented in this paper by proposing a fuzzy relational inner composition. This leads to an integrated framework for representing multilevel fuzzy relational equations which is able to provide multi-dimensional models of complex systems very effectively. A potentially online derivative-based identification algorithm is also presented for the proposed model. The identification procedure is based on the special t-norm-based and t-conorm-based operations leading to an easy and fast implementation of the proposed algorithm. The proposed modeling structure is customized and used for two different applications. The simulation results show high modeling capability of the proposed fuzzy relational model. [ABSTRACT FROM AUTHOR]

Background: Although Pneumatic Artificial Muscle (PAM) has a promising future in rehabilitation robots, it's difficult to realize accurate position control due to its highly nonlinear properties.Objective: This paper deals with position control of PAM.Methods: To describe the hysteresis inside PAM, a polynomial based phenomenological function is developed. Based on the phenomenological model for PAM and analysis of pressure dynamics within PAM, an adaptive cascade controller is proposed. Both outer loop and inner loop employ BP Neural Network tuned PID algorithm. The outer loop is to handle high nonlinearities and unmodeled dynamics of PAM, while the inner loop is responsible for nonlinearities caused by pressure dynamics.Results: Experimental results show high tracking accuracy as compared with a convention PID controller.Conclusion: The proposed controller is effective in improving performance of PAM and will be implemented in a rehabilitation robot. [ABSTRACT FROM AUTHOR]

For many practical applications of ASP, for instance data integration or planning, query answering is important, and therefore query optimization techniques for ASP are of great interest. Magic Sets are one of these techniques, originally defined for Datalog queries (ASP without disjunction and negation). Dynamic Magic Sets (DMS) are an extension of this technique, which has been proved to be sound and complete for query answering over ASP programs with stratified negation. A distinguishing feature of DMS is that the optimization can be exploited also during the non-deterministic phase of ASP engines. In particular, after some assumptions have been made during the computation, parts of the program may become irrelevant to a query under these assumptions. This allows for dynamic pruning of the search space, which may result in exponential performance gains. In this paper, the correctness of DMS is formally established and proved for brave and cautious reasoning over the class of super-coherent ASP programs (ASPsc programs). ASPsc programs guarantee consistency (i.e., have answer sets) when an arbitrary set of facts is added to them. This result generalizes the applicability of DMS, since the class of ASPsc programs is richer than ASP programs with stratified negation, and in particular includes all odd-cycle-free programs. DMS has been implemented as an extension of DLV, and the effectiveness of DMS for ASPsc programs is empirically confirmed by experimental results with this system. [ABSTRACT FROM AUTHOR]

Background: Efficient mid-range wireless power transfer between transmitter and the receiver has been achieved based on the magnetic resonant coupling method. The influence of electromagnetic field on the human body due to resonant wireless power transfer system (RWPT) should be taken into account during the design process of the system.Objective: To analyze the transfer performance of the RWPT system and the change rules of the specific absorption rate (SAR) in the human head model due to the RWPT system.Methods: The circuit-field coupling method for a RWPT system with consideration of the displacement current was presented. The relationship between the spiral coil parameters and transfer performance was studied. The SAR in the human head model was calculated under two different exposure conditions.Results: A system with output power higher than 10 W at 0.2 m distance operating at a frequency of approximately 1 MHz was designed. The FEM simulation results show the peak SAR value is below the safety limit which appeared when the human head model is in front of the transmitter.Conclusion: The simulation results agreed well with the experimental results, which verified the validity of the analysis and design. [ABSTRACT FROM AUTHOR]

BACKGROUND: Most existing models/algorithms for simulating goal-directed human motions were designed to generate a single "realistic" motion for a given input scenario. OBJECTIVE: This study presents a novel reach motion generation algorithm utilizing multiple posture memories. The algorithm aims to compute and visualize a set of human reach motions that approximates the full range of physically and physiologically feasible human motions for a given input scenario. METHODS: The algorithm utilizes posture memories constructed specifically for an individual worker using a probabilistic posture generation and registration process. The posture memories relate a hand position to the set of postures that place the individual's hand in its vicinity. When given an input scenario, the algorithm first generates different hand paths connecting the starting and ending hand positions specified in the scenario. Then, for each hand path, the algorithm produces different "feasible" motions by selecting and connecting multiple postures stored in the posture memories; the postures corresponding to the hand positions along the hand path are utilized. CONCLUSIONS: The proposed algorithm helps understand the impacts of workplace design on the range of feasible human motion behaviors, and, thereby, contributes to the computer-aided ergonomics design of work tasks and workplaces. [ABSTRACT FROM AUTHOR]