APF-RL: Safe Mapless Navigation in Unknown Environments
Author:
Affiliation:
1. Electrical & Electronics Engineering, Boğaziçi University,Intelligent Systems Laboratory,Istanbul,Turkey
Funder
The Scientific and Technological Research Council of Turkey (TUBITAK)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9811522/9811357/09811537.pdf?arnumber=9811537
Reference39 articles.
1. Continuous control with deep reinforcement learning;lillicrap;CoRR,0
2. From perception to decision: A data-driven approach to end-to-end motion planning for autonomous ground robots
3. A survey of deep learning techniques for autonomous driving
4. Sensor-Based Reactive Symbolic Planning in Partially Known Environments
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1. Learning Autonomous Navigation in Unmapped and Unknown Environments;Sensors;2024-09-12
2. PathRL: An End-to-End Path Generation Method for Collision Avoidance via Deep Reinforcement Learning;2024 IEEE International Conference on Robotics and Automation (ICRA);2024-05-13
3. An assistive robot in healthcare scenarios requiring monitoring and rules regulation: exploring Pepper use case;2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM);2023-12-05
4. DVT-Tree: Dynamic Visible Topology Tree for Efficient Mapless Navigation in Maze Environments;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24
5. Social APF-RL: Safe Mapless Navigation in Unknown & Human-Populated Environments;2023 European Conference on Mobile Robots (ECMR);2023-09-04
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