Collaborative route map and navigation of the guide dog robot based on optimum energy consumption

The guide dog robot (GDR) is a low-speed companion robot that serves visually impaired people and is used to guide blind people to walk steadily, carrying a variety of intelligent technologies and needing to have the ability to guide with optimal energy consumption in specific scenarios. This paper proposes an innovative technique for virtual-real collaborative path planning and navigation of the GDR specific indoor scenarios, and designs an experimental method for virtual-real collaborative path planning of the GDR specific scenarios. The energy consumption integral equation is used to solve for the energy consumption of the GDR with virtual-real synergy, and the difference in energy consumption is compared for three different navigation directions: horizontal, vertical and oblique obstacle avoidance. The results show that the optimized GDR saves 6.91% in rectilinear movement and 10.60% in curved movement. The efficiency of planning and navigating the GDR in specific domestic scenarios is verified by a virtual-real cooperative. The realization of optimal path planning for energy consumption is instrumental in exploring many of the most significant thought in the path planning and navigation of mobile robots in indoor specific scenarios.