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To ensure accurate position and force control of massage robot working on human body with unknown skin characteristics, this study aims to propose a novel intelligent impedance control system.

First, a skin dynamic model (SDM) is introduced to describe force-deformation on the human body as feed-forward for force control. Then a particle swarm optimization (PSO) method combined with graph-based knowledge transfer learning (GKT) is studied, which will effectively identify personalized skin parameters. Finally, a self-tuning impedance control strategy is designed to accommodate uncertainty of skin dynamics, system delay and signal noise exist in practical applications.

Compared with traditional least square method, genetic algorithm and other kinds of PSO methods, combination of PSO and GKT is validated using experimental data to improve the accuracy and convergence of identification results. The force control is effective, although there are contour errors, control delay and noise problems when the robot does massage on human body.

Integrating GKT into PSO identification algorithm, and designing an adaptive impedance control algorithm. As a result, the robot can understand textural and biological attributes of its surroundings and adapt its planning activities to carry out a stable and accurate force tracking control during dynamic contacts between a robot and a human.

This study aims to explore the impact of high-performance work systems (HPWS) on open innovation and the moderating role of information technology (IT) capability on the relationship between HPWS and open innovation.

This study conducted a questionnaire survey in the industrial parks of the Yangzi River Delta in China and obtained 108 useful responses.

HPWS positively impacts open innovation. IT exploration capability strengthens the relationship between HPWS and open innovation, whereas IT exploitation capability and ambidexterity do not strengthen such relationship.

Firms should use HPWS to improve employees' motivation of external learning and searching for enhancing innovation openness. They should acknowledge the enabling role of IT exploration capability in facilitating employees' learning and searching toward open innovation and discreetly develop IT exploitation capability and ambidexterity during external knowledge searching, which may not achieve the desired facilitation purpose.

This study contributes to human resource management (HRM) by suggesting that a new antecedent, which is HPWS in our case, should be taken into account when considering the influence of HRM in the process of open innovation. This study has important implications for HPWS, IT capability and open innovation; open innovation can be improved by using HPWS and IT capability. This study also expands IT ambidexterity to HRM and innovation studies.