Abstract
The navigation system is a key module in the future application of mobile robots and is essential for the safety and robustness of mobile robot motion. Available navigation systems can already perform reasonable path planning and motion planning processes in specific scenarios. However, with the development of mobile robotics, there are higher requirements for the scenarios in which the robots operate and the response efficiency requirements. In order to solve the problem of motion planning and obstacle avoidance between path points in dynamic campus scenes, a combination of static obstacle avoidance based on voxel grid and dynamic obstacle avoidance based on MPCC is proposed on Ackermann kinematic model as well as motion control. The organic combination of static obstacle avoidance and dynamic obstacle avoidance solves the problem of quickly performing path planning and obstacle avoidance for unmanned vehicles in complex environments. The work has been experimented on simulation conditions and actual robots, and the robots have been placed in campus scenarios for validation.
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This work was supported by the National Natural Science Found of china (Grant No. 62103393).
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Chen, Z., Chen, L., Zhao, G., Wang, J. (2022). A Campus Scene Navigation Scheme Based on MPCC Dynamic Obstacle Avoidance Method. In: Fan, W., Zhang, L., Li, N., Song, X. (eds) Methods and Applications for Modeling and Simulation of Complex Systems. AsiaSim 2022. Communications in Computer and Information Science, vol 1713. Springer, Singapore. https://doi.org/10.1007/978-981-19-9195-0_10
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DOI: https://doi.org/10.1007/978-981-19-9195-0_10
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