Rapidly exploring learning trees

Rapidly exploring learning trees

Inverse Reinforcement Learning (IRL) for path planning enables robots to learn cost functions for difficult tasks from demonstration, instead of hard-coding them. However, IRL methods face practical limitations that stem from the need to repeat costly planning procedures. In this paper, we propose R...

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Bibliografiske detaljer
Main Authors:	Shiarlis, K, Messias, J, Whiteson, S
Format:	Conference item
Udgivet:	IEEE 2017

Lignende værker

Inverse reinforcement learning from failure
af: Shiarlis, K, et al.
Udgivet: (2016)

TACO: Learning task decomposition via temporal alignment for control
af: Shiarlis, K, et al.
Udgivet: (2018)

Dynamic-depth context tree weighting
af: Messias, J, et al.
Udgivet: (2018)

Learning from demonstration in the wild
af: Behbahani, F, et al.
Udgivet: (2019)

VariBAD: a very good method for Bayes-adaptive deep RL via meta-learning
af: Zintgraf, L, et al.
Udgivet: (2020)

Phototropism rapidly exploring random tree: An efficient rapidly exploring random tree approach based on the phototropism of plants
af: Chengchen Zhuge, et al.
Udgivet: (2020-09-01)

Optimal Bidirectional Rapidly-Exploring Random Trees
af: Jordan, Matthew, et al.
Udgivet: (2013)

Parallel Quantum Rapidly-Exploring Random Trees
af: Paul Lathrop, et al.
Udgivet: (2024-01-01)

Autonomous Rear Parking via Rapidly Exploring Random-Tree-Based Reinforcement Learning
af: Saugat Shahi, et al.
Udgivet: (2022-09-01)

TreeQN and ATreeC: differentiable tree planning for deep reinforcement learning
af: Farquhar, G, et al.
Udgivet: (2018)

Robotic path planning using rapidly-exploring random trees
af: Sherwani, Fahad
Udgivet: (2013)

Recent advances in Rapidly-exploring random tree: A review
af: Tong Xu
Udgivet: (2024-06-01)

Rapidly-exploring Random Belief Trees for Motion Planning Under Uncertainty
af: Bry, Adam P.
Udgivet: (2011)

Improved rapidly exploring random tree using salp swarm algorithm
af: Muhsen Dena Kadhim, et al.
Udgivet: (2024-03-01)

Systematic Literature Review of Sampling Process in Rapidly-Exploring Random Trees
af: Luiz Gustavo D. O. Veras, et al.
Udgivet: (2019-01-01)

Bounds on tracking error using closed-loop rapidly-exploring random trees
af: Luders, Brandon Douglas, et al.
Udgivet: (2010)

Research on risk detection of autonomous vehicle based on rapidly-exploring random tree
af: Yincong Ma, et al.
Udgivet: (2023)

Simplified and Smoothed Rapidly-Exploring Random Tree Algorithm for Robot Path Planning
af: Ayhan Gültekin, et al.
Udgivet: (2023-01-01)

Efficient Path Planning Based on Dynamic Bridging Rapidly Exploring Random Tree
af: Shulei Qiu, et al.
Udgivet: (2024-02-01)

Research on Risk Detection of Autonomous Vehicle Based on Rapidly-Exploring Random Tree
af: Yincong Ma, et al.
Udgivet: (2023-03-01)

Adaptive Path Planning for Fusing Rapidly Exploring Random Trees and Deep Reinforcement Learning in an Agriculture Dynamic Environment UAVs
af: Gabriel G. R. de Castro, et al.
Udgivet: (2023-01-01)

Robotic Active Information Gathering for Spatial Field Reconstruction with Rapidly-Exploring Random Trees and Online Learning of Gaussian Processes
af: Alberto Viseras, et al.
Udgivet: (2019-02-01)

Information-rich Path Planning with General Constraints using Rapidly-exploring Random Trees
af: Levine, Daniel S., et al.
Udgivet: (2010)

Modeling UAV swarm flight trajectories using Rapidly-exploring Random Tree algorithm
af: Jan M. Kelner, et al.
Udgivet: (2024-01-01)

Rapidly Exploring Random Tree Algorithm-Based Path Planning for Worm-Like Robot
af: Yifan Wang, et al.
Udgivet: (2020-06-01)

A survey of path planning of industrial robots based on rapidly exploring random trees
af: Sha Luo, et al.
Udgivet: (2023-11-01)

Information-rich path planning under general constraints using Rapidly-exploring Random Trees
af: Levine, Daniel S., Ph. D. Massachusetts Institute of Technology.
Udgivet: (2010)

Decentralized path planning for multiple agents in complex environments using rapidly-exploring random trees
af: Desaraju, Vishnu R. (Vishnu Rajeswar)
Udgivet: (2011)

A safe overtaking control scheme for autonomous vehicles using rapid-exploration random tree
af: Yincong Ma, et al.
Udgivet: (2022)

Ship path planning and tracking based on rapidly exploring random tree star and convex optimization
af: Chang ZHOU, et al.
Udgivet: (2025-02-01)

A Systematic Review of Rapidly Exploring Random Tree RRT Algorithm for Single and Multiple Robots
af: Muhsen Dena Kadhim, et al.
Udgivet: (2024-09-01)

Memorized Rapidly Exploring Random Tree Optimization (MRRTO): An Enhanced Algorithm for Robot Path Planning
af: Muhsen Dena Kadhim, et al.
Udgivet: (2024-03-01)

Development of an Improved Rapidly Exploring Random Trees Algorithm for Static Obstacle Avoidance in Autonomous Vehicles
af: S. M. Yang, et al.
Udgivet: (2021-03-01)

LAC-RRT: Constrained Rapidly-Exploring Random Tree With Configuration Transfer Models for Motion Planning
af: Chi-Kai Ho, et al.
Udgivet: (2023-01-01)

Path Planning Algorithm Using the Hybridization of the Rapidly-Exploring Random Tree and Ant Colony Systems
af: Muhammad Aria Rajasa Pohan, et al.
Udgivet: (2021-01-01)

Extended rapidly exploring random tree–based dynamic path planning and replanning for mobile robots
af: Devin Connell, et al.
Udgivet: (2018-05-01)

RRT-Based Optimizer: A Novel Metaheuristic Algorithm Based on Rapidly-Exploring Random Trees Algorithm
af: Guang-Jin Lai, et al.
Udgivet: (2025-01-01)

Automation of autonomous mobile robot docking based on the counter growth rapidly exploring random tree method
af: V. V. Golubov, et al.
Udgivet: (2024-02-01)

Features and perspectives of application of the rapidly exploring random tree method for motion planning of autonomous robotic manipulators
af: V. V. Golubov, et al.
Udgivet: (2023-12-01)

Hierarchical Path-Planning for Mobile Robots Using a Skeletonization-Informed Rapidly Exploring Random Tree*
af: Hyejeong Ryu
Udgivet: (2020-11-01)