This study advances research on high‐commitment work systems (HCWSs) and organizational innovation by examining how the configuration of middle managers' work–family issues (i.e., work–family conflict and work climate for sharing family concerns) shape the relationship between HCWSs and innovation performance. Using a matched sample of senior management team members, middle managers, and frontline employees from 113 Chinese manufacturing firms and two waves of survey, we found that HCWSs are associated with enhanced levels of middle managers' innovative behavior, an association that improves innovation performance. The results also show that high levels of work–family conflict weaken the relationship between HCWSs and innovative behavior, but can be attenuated when a work climate better facilitates the sharing of family concerns. The study contributes to the knowledge of the role of HCWSs and contextual conditions of their effects in enhancing organizational innovation performance, with specific implications for the Chinese context.

The cooperative path planning problem of multiple mobile robots in an unknown indoor environment is considered in this article. We presented a novel obstacle avoidance and real-time navigation algorithm. The proposed approach consisted of global path planning and local path planning via HAFSA (hybrid artificial fish swarm algorithm) and an expansion logic strategy. Meanwhile, a kind of scoring function was developed, which shortened the time of local path planning and improved the decision-making ability of the path planning algorithm. Finally, using STDR (simple two dimensional robot simulator) and RVIZ (robot operating system visualizer), a multiple mobile robot simulation platform was designed to verify the presented real-time navigation algorithm. Simulation experiments were performed to validate the effectiveness of the proposed path planning method for multiple mobile robots.

Aiming at the strong dependence on environmental information in traditional algorithms, the path planning of basketball robots in an unknown environment, and improving the safety of autonomous navigation, this article proposes a path planning algorithm based on behavior-based module control. In this article, fuzzy control theory is applied to the behavior control structure, and these two path planning algorithms are combined to solve the path planning problem of basketball robots in an unknown environment. First, the data of each sensor of the basketball robot configuration are simply fused. Then, the obstacle distance parameters in the three directions of front, left, and right are simplified and fuzzified. Then combined with the target direction parameters, the speed, and steering of the basketball robot are controlled by fuzzy rule reasoning to realize path planning. The simulation results show that the basketball robot can overcome the uncertainty in the environment, effectively achieve good path planning, verify the feasibility of the fuzzy control algorithm, and demonstrate the validity and correctness of the path planning strategy.

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