@inproceedings{0de53fdf0ba7476db2659e2e8fbf1dd3,
title = "Path Planning and Simulation Based on Cumulative Error Estimation",
abstract = "Path planning plays a significant role in robot navigation applications, as path exploration ability requires the knowledge of both the kinematics and the environments. Most of the current methods consider the planning process alone instead of combining the planning results with tracking control, which leads to a significant reduction in the availability of the path, especially in complex scenarios with missing GPS and low positioning sensor accuracy. This paper proposes a reinforcement learning-based path planning algorithm, which aims to consider the errors caused by the robot{\textquoteright}s motion during the dead-reckoning process and effectively reduces the cumulative error within the optimization process. The simulation conclusion in the 2D scene verifies the effectiveness of the algorithm for reducing the cumulative error.",
keywords = "Cumulative error estimation, Path planning, Reinforcement learning",
author = "Can Wang and Chensheng Cheng and Dianyu Yang and Feihu Zhang and Guang Pan",
note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Singapore Pte Ltd.; 5th International Conference on Cognitive Systems and Signal Processing, ICCSIP 2020 ; Conference date: 25-12-2020 Through 27-12-2020",
year = "2021",
doi = "10.1007/978-981-16-2336-3_12",
language = "英语",
isbn = "9789811623356",
series = "Communications in Computer and Information Science",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "131--141",
editor = "Fuchun Sun and Huaping Liu and Bin Fang",
booktitle = "Cognitive Systems and Signal Processing - 5th International Conference, ICCSIP 2020, Revised Selected Papers",
}