1 |
Hornung Armin, Phillips M, Gil Jones E, et al. Navigation in Three-dimensional Cluttered Environments for Mobile Manipulation[C]//2012 IEEE International Conference on Robotics and Automation. Piscataway, NJ, USA: IEEE, 2012: 423-429.
|
2 |
晋晓飞, 王浩, 宗卫佳, 等. 自主移动机器人避障技术研究现状[J]. 传感器与微系统, 2018, 37(5): 5-9.
|
|
Jin Xiaofei, Wang Hao, Zong Weijia, et al. Research Status of Obstacle Avoidance Technologies for Autonomous Mobile Robots[J]. Transducer and Microsystem Technologies, 2018, 37(5): 5-9.
|
3 |
Lee H Y, Ho H W, Zhou Y. Deep Learning-based Monocular Obstacle Avoidance for Unmanned Aerial Vehicle Navigation in Tree Plantations[J]. Journal of Intelligent & Robotic Systems, 2021, 101(1): 5.
|
4 |
Sina Sharif Mansouri, Karvelis Petros, Kanellakis Christoforos, et al. Vision-based MAV Navigation in Underground Mine Using Convolutional Neural Network[C]//IECON 2019-45th Annual Conference of the IEEE Industrial Electronics Society. Piscataway, NJ, USA: IEEE, 2019: 750-755.
|
5 |
Manderson Travis, Juan Camilo Gamboa Higuera, Cheng Ran, et al. Vision-based Autonomous Underwater Swimming in Dense Coral for Combined Collision Avoidance and Target Selection[C]//2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ, USA: IEEE, 2018: 1885-1891.
|
6 |
Loquercio Antonio, Maqueda Ana I, del-Blanco Carlos R, et al. DroNet: Learning to Fly by Driving[J]. IEEE Robotics and Automation Letters, 2018, 3(2): 1088-1095.
|
7 |
Tai Lei, Li Shaohua, Liu Ming. A Deep-network Solution Towards Model-less Obstacle Avoidance[C]//2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ, USA: IEEE, 2016: 2759-2764.
|
8 |
Liu Canglong, Zheng Bin, Wang Chunyang, et al. CNN-based Vision Model for Obstacle Avoidance of Mobile Robot[C]//2017 3rd International Conference on Mechanical, Electronic and Information Technology Engineering. France: EDP Sciences, 2017: 7.
|
9 |
金彦亮, 朱容廷. 机器人端到端视觉避障方法研究[J]. 工业控制计算机, 2019, 32(9): 77-79.
|
|
Jin Yanliang, Zhu Rongting. Research on Robot End-to-end Visual Obstacle Avoidance Method[J]. Industrial Control Computer, 2019, 32(9): 77-79.
|
10 |
Michels J, Saxena A, Ng A Y. High Speed Obstacle Avoidance Using Monocular Vision and Reinforcement Learning[C]//Proceedings of the 22nd International conference on Machine learning. New York, NY, USA: Association for Computing Machinery, 2005: 593-600.
|
11 |
Xie L, Wang S, Markham A, et al. Towards Monocular Vision Based Obstacle Avoidance Through Deep Reinforcement Learning[C]//Robotics: Science and Systems (RSS 2017) Workshop. Boston, MA, USA: MIT, 2017: 1-6.
|
12 |
Guldenring Ronja, Görner Michael, Hendrich Norman, et al. Learning Local Planners for Human-aware Navigation in Indoor Environments[C]//2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ, USA: IEEE, 2020: 6053-6060.
|
13 |
Craig Coulter R. Implementation of the Pure Pursuit Path Tracking Algorithm: CMU-RI-TR-92-01[R]. Pittsburgh, PA, USA: Carnegie Mellon University, 1992: 1-15.
|
14 |
Zhang Chao, Yang Zichao, He Xiaodong, et al. Multimodal Intelligence: Representation Learning, Information Fusion, and Applications[J]. IEEE Journal of Selected Topics in Signal Processing, 2020, 14(3): 478-493.
|
15 |
Hochreiter Sepp, Schmidhuber Jürgen. Long Short-term Memory[J]. Neural Computation, 1997, 9(8): 1735-1780.
|
16 |
Koenig N, Howard A. Design and Use Paradigms for Gazebo, an Open-source Multi-robot Simulator[C]//2004 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). Piscataway, NJ, USA: IEEE, 2004: 2149-2154.
|
17 |
Liu Yuzhou, Novotny Georg, Smirnov Nikita, et al. Mobile Delivery Robots: Mixed Reality-based Simulation Relying on ROS and Unity 3D[C]//2020 IEEE Intelligent Vehicles Symposium (IV). Piscataway, NJ, USA: IEEE, 2020: 15-20.
|
18 |
Katara Pushkal, Khanna Mukul, Nagar Harshit, et al. Open Source Simulator for Unmanned Underwater Vehicles Using ROS and Unity3D[C]//2019 IEEE Underwater Technology (UT). Piscataway, NJ, USA: IEEE, 2019: 1-7.
|
19 |
Konrad A. Simulation of Mobile Robots with Unity and Ros: A Case-study and a Comparison with Gazebo[D]. Trollhättan, Sweden: University West, 2019.
|