reinforcement-learningmodel-predictive-controlmodel-based-rlderivative-free-optimizationsampling-based-planning UpdatedOct 20, 2020 Python yiyunevin/RL-RRT-Local-Planner Star49 A ROS package of a autonomous navigation method based on SAC and Bidirectional RRT* (Repository RL-RRT-Global-Planner). ...
The search space can be extremely large which cannot be exhaustively searched in near-real time for motion planning of autonomous vehicles. Hence, samples may be drawn out from the search space to reduce the volume of search space to a selected few samples only, and planning may be performed...
RL agents are used to control the robot under the direction of planning, enabling long-range navigation 【RL通过其来规划方向?从而实现长距离,emmm 传统的PRM在这里的劣势是太长了规划时间太长嘛?那RL的学习也不见得很快...】 I. Introduction
新鲜出炉的运动规划论文,Learning to Predict Ego-Vehicle Poses for Sampling-Based Nonholonomic Motion Planning,来自博世下属研究机构。 该文在技术上并没有太大创新,但是为解决non-holonomic机器人/汽车的运动规划问题提供了一个相当有趣的角度。针对对环境适应性和安全性要求极高的自动驾驶问题,基于采样的运动规划很...
本文记录:Integrating Fast Regional Optimization into Sampling-based Kinodynamic Planning for Multirotor Flight,Hongkai Ye1;2, Tianyu Liu3, Chao Xu1;2 and Fei Gao1;2。作者表示本文是对之前的工作ref[…
We consider the problem of leveraging prior experience to generate roadmaps in sampling-based motion planning. A desirable roadmap is one that is sparse, allowing for fast search, with nodes spread out at key locations such that a low- cost feasible path exists. An increasingly popular approach...
sampling-based-path-planning RRT and Pruning RRT is a path planning algorithm based on random sampling. It can search the whole state space quickly and is widely used to the high-dimensional problems. Pruning is a simple but efficient algorithm thought.It's intention is to avoid unnecessary sea...
Bialkowski, J., Karaman, S., Otte, M., Frazzoli, E.: Efficient collision checking in sampling-based motion planning. In: WAFR. pp. 365-380 (2012)J. Bialkowski, S. Karaman, M. Otte, and E. Frazzoli, "Efficient collision checking in sampling-based motion planning," in WAFR, 2012, ...
a feasible path can be found without the complex geometric modeling of the configuration space. However, the quality of the initial solution is not guaranteed, and the convergence speed to the optimal solution is slow. In this paper, we present a novel image-based path planning algorithm to o...
To address this issue, this paper proposes a sampling-based trajectory planning method with a hierarchical structure for formation flight in dense obstacle environments. To ensure reliable local sensing information sharing among UAVs, each UAV generates a safe flight corridor (SFC), which is ...