Indoor mobile robot human-machine integration navigation device and method

Abstract

The invention discloses an indoor mobile robot human-machine integration navigation device and method. The device comprises a pedestrian modeling module, a dynamic cost map, a global path planner, a robot and an indoor vision sensor. The pedestrian modeling module is used for converting the pedestrian perception information into a cost map required by the global path planner search map. The dynamic cost map provides the global path planner with the information of social constraints in the future. The global path planner is the core of the whole system and is responsible for receiving the navigation target pose and the AMCL positioning information, using the "planning-prediction-execution" time series period to carry out dynamic planning and building the search map based on the dynamic cost map to calculate the optimal planning result of the current planning period in each planning period. The robot and the indoor vision sensor are responsible for global environmental perception. In addition, the robot moving chassis receives the underlying motion commands for mobile navigation. The device and the method can be effectively and flexibly applied to the actual indoor environment.

Description

Technical field: [0001] The invention relates to a human-machine fusion navigation device and method for an indoor mobile robot, and belongs to the technical field of human-machine fusion navigation for indoor environments of mobile robots. Background technique: [0002] With the rapid development of mobile robots, mobile robots have been widely used in various service places. Among them, human-machine fusion navigation aims to improve social ability and follow social norms during robot navigation, which has attracted extensive research attention. Human-machine fusion navigation needs to meet comfort and social requirements. Comfort requires maintaining an appropriate distance and adopting an appropriate approach strategy. Social requirements require robots to follow social norms, such as setting to the right and avoiding passing through a group of people. [0003] 1. Path planning technology is the core technology of mobile robot operation. In a working environment with ob...

AI Technical Summary

Problems solved by technology

The classic models of pedestrian modeling include Proxemics and Social force models. The former is often used for comfort distance modeling but cannot model pedestrian motion. The latter establishes a kinematics model for pedestrians. Carry out motion modeling, but the disadvantage of this model is that it relies on all pedestrian information in the environment; many scholars model pedestrian intentions, such as pedestrian interaction intention recognition based on Bayesian theory, pedestrian movement target point reasoning, etc., but intention recognition There are problems such as complexity and randomness. Therefore, most of the current human-machine fusion navigation is based on motion modeling, such as classifying and learning pedestrian motion patterns, using trajectory prediction to improve path planning methods, etc.

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