A review of mobile robot motion planning methods: from classical motion planning workflows to reinforcement learning-based architectures

L Dong, Z He, C Song, C Sun - Journal of Systems Engineering …, 2023 - ieeexplore.ieee.org
Motion planning is critical to realize the autonomous operation of mobile robots. As the
complexity and randomness of robot application scenarios increase, the planning capability …

Multigoal visual navigation with collision avoidance via deep reinforcement learning

W ** and navigation method in complex construction environments
T Ren, H Jebelli - Computer‐Aided Civil and Infrastructure …, 2024 - Wiley Online Library
Recent advancements in construction robotics have significantly transformed the
construction industry by delivering safer and more efficient solutions for handling complex …

Semantic-driven autonomous visual navigation for unmanned aerial vehicles

P Yue, J **n, Y Zhang, Y Lu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Aiming at the autonomous navigation of unmanned aerial vehicles (UAVs) in complex and
unknown environments, this article combines transfer reinforcement learning theory with an …

SkillTree: Explainable Skill-Based Deep Reinforcement Learning for Long-Horizon Control Tasks

Y Wen, S Li, R Zuo, L Yuan, H Mao, P Liu - arxiv preprint arxiv …, 2024 - arxiv.org
Deep reinforcement learning (DRL) has achieved remarkable success in various research
domains. However, its reliance on neural networks results in a lack of transparency, which …

Reinforcement and curriculum learning for off-road navigation of an UGV with a 3D LiDAR

M Sánchez, J Morales, JL Martínez - Sensors, 2023 - mdpi.com
This paper presents the use of deep Reinforcement Learning (RL) for autonomous
navigation of an Unmanned Ground Vehicle (UGV) with an onboard three-dimensional (3D) …

Autonomous navigation of mobile robots in unknown environments using off-policy reinforcement learning with curriculum learning

Y Yin, Z Chen, G Liu, J Yin, J Guo - Expert Systems with Applications, 2024 - Elsevier
Reinforcement learning (RL) is effective for autonomous navigation tasks without prior
knowledge of the environment. However, traditional mobile robot navigation algorithms …

Multiple Self-Supervised Auxiliary Tasks for Target-Driven Visual Navigation Using Deep Reinforcement Learning

W Zhang, L He, H Wang, L Yuan, W **ao - Entropy, 2023 - mdpi.com
Visual navigation based on deep reinforcement learning requires a large amount of
interaction with the environment, and due to the reward sparsity, it requires a large amount …