This system demonstrates real-time navigation and accurate positioning in indoor mobile robots, suggesting improvements in autonomous driving.
Currently, the rapid development of computer and robotics technology has led to robots gradually entering people's daily lives, and service-oriented indoor mobile robots have received widespread attention. Positioning and navigation are the core issues in researching indoor robots. This system is based on SC-LIO-SAM, which studies map modeling, accurate robot positioning, and real-time path planning. Through three steps of establishing a map, modifying the map, and actual navigation, the system is debugged and the results meet the predetermined goals. This system has a good reference value for researching robot positioning, autonomous driving, and automatic control.
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Chen et al. (2025) studied this question.
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