In recent years, the path planning of robot has been a hot research direction, and multirobot formation has practical application prospect in our life. This article proposes a hybrid path planning algorithm applied to robot formation. The improved Rapidly Exploring Random Trees algorithm PQ-RRT ∗ with new distance evaluation function is used as a global planning algorithm to generate the initial global path. The determined parent nodes and child nodes are used as the starting points and target points of the local planning algorithm, respectively. The dynamic window approach is used as the local planning algorithm to avoid dynamic obstacles. At the same time, the algorithm restricts the movement of robots inside the formation to avoid internal collisions. The local optimal path is selected by the evaluation function containing the possibility of formation collision. Therefore, multiple mobile robots can quickly and safely reach the global target point in a complex environment with dynamic and static obstacles through the hybrid path planning algorithm. Numerical simulations are given to verify the effectiveness and superiority of the proposed hybrid path planning algorithm.

This document explains and demonstrates from the elderly, intelligent medical service market capacity and the development status of intelligent medical service system in three aspects of the elderly intelligent medical industry market development background analysis, put forward on the basis of intelligent medical industry development path of the elderly. The study found that the elderly medical service market capacity is large, intelligent medical service system needs to be improved. Recommends that the government strengthen the construction of the elderly medical service system, improve top-level design, promote the medical service system and pension services industry collaborative development; enterprises take advantage of policy, try to launch pilot services, supporting the development of services, the integration of data sources, the formation of health data system, improve the status quo of intelligent medical service.