An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning
Stanford University（斯坦福大学）；Carlos III University of Madrid（马德里卡洛斯三世大学）
Joseph A. Starek, Javier V. Gomez, Edward Schmerling, Lucas Janson, Luis Moreno, Marco Pavone
备注：
Accepted to the 2015 IEEE Intelligent Robotics and Systems Conference in Hamburg, Germany. This submission represents the long version of the conference manuscript, with additional proof details (Section IV) regarding the asymptotic optimality of the BFMT* algorithm
Bi-directional search is a widely used strategy to increase the success and convergence rates of sampling-based motion planning algorithms. Yet, few results are available that merge both bi-directional search and asymptotic optimality into existing optimal planners, such as PRM*, RRT*, and FMT*. The objective of this paper is to fill this gap. Specifically, this paper presents a bi-directional, sampling-based, asymptotically-optimal algorithm named Bi-directional FMT* (BFMT*) that extends the Fast Marching Tree (FMT*) algorithm to bi-directional search while preserving its key properties, chiefly lazy search and asymptotic optimality through convergence in probability. BFMT* performs a two-source, lazy dynamic programming recursion over a set of randomly-drawn samples, correspondingly generating two search trees: one in cost-to-come space from the initial configuration and another in cost-to-go space from the goal configuration. Numerical experiments illustrate the advantages of BFMT* over its unidirectional counterpart, as well as a number of other state-of-the-art planners.
Department of Cybernetics, Czech Technical University in Prague（捷克技术大学布拉格分校自动化系）；Mechanical and Aerospace Engineering, Old Dominion University（旧 Dominion 大学机械与航空航天工程系）；Mechanical Engineering Faculty, Sahand University of Technology（沙赫德大学机械工程系）；Aksaray University（阿克萨雷大学）
Asymptotically Optimal Lazy Lifelong Sampling-based Algorithm for Efficient Motion Planning in Dynamic Environments
Department of Mechanical Engineering, City University of Hongkong（机械工程系，香港城市大学）；Department of Electronic and Electrical Engineering, Southern University of Science and Technology（电子与电气工程系，南方科技大学）；Department of Electronic and Computer Engineering, Hong Kong University of Science and Technology（电子与计算机工程系，香港科技大学）
Multi-Risk-RRT: An Efficient Motion Planning Algorithm for Robotic Autonomous Luggage Trolley Collection at Airports
Southern University of Science and Technology（南方科技大学）；Jiaxing Research Institute, Southern University of Science and Technology（南方科技大学嘉兴研究院）；University of Pennsylvania（宾夕法尼亚大学）；Shanghai Jiao Tong University（上海交通大学）；Yanshan University（燕山大学）
Nearest-Neighbourless Asymptotically Optimal Motion Planning with Fully Connected Informed Trees (FCIT*)
Estimation, Search, and Planning (ESP) Research Group, Queen’s University, Kingston ON, Canada（皇后大学估计、搜索与规划研究组）；Department of Computer Science, Rice University, Houston TX, USA（里士满大学计算机科学系）；Department of Computer Science, Purdue University, West Lafayette IN, USA（普渡大学计算机科学系）；Ken Kennedy Institute, Rice University, Houston TX, USA（里士满大学肯尼迪研究所）
Generalizing Informed Sampling for Asymptotically Optimal Sampling-based Kinodynamic Planning via Markov Chain Monte Carlo
Robotics Institute, Carnegie Mellon University（卡内基梅隆大学机器人研究所）；Paul G. Allen School of Computer Science & Engineering, University of Washington（华盛顿大学保罗·G·艾伦计算机科学与工程学院）
Potentially Guided Bidirectionalized RRT* for Fast Optimal Path Planning in Cluttered Environments
National University of Sciences And Technology (NUST)（国立科技大学）；University of California San Diego（加州大学圣迭戈分校）；Manchester Metropolitan University (MMU)（曼彻斯特城市大学）
NAMR-RRT: Neural Adaptive Motion Planning for Mobile Robots in Dynamic Environments
Southern University of Science and Technology（南方科技大学）；Jiaxing Research Institute, Southern University of Science and Technology（南方科技大学嘉兴研究院）；Peng Cheng National Laboratory（鹏城国家实验室）；Harbin Institute of Technology Shenzhen（哈尔滨工业大学深圳校区）
Relevant Region Sampling Strategy with Adaptive Heuristic for Asymptotically Optimal Path Planning
The Chinese University of Hong Kong（香港中文大学）；Southern University of Science and Technology（南方科技大学）；Shenzhen Research Institute of the Chinese University of Hong Kong（香港中文大学深圳研究院）
Informed Sampling for Asymptotically Optimal Path Planning (Consolidated Version)
Carnegie Mellon University（卡内基梅隆大学）；Massachusetts Institute of Technology（麻省理工学院）；University of Toronto（多伦多大学）；University of Waterloo（滑铁卢大学）；University of Toronto Institute for Aerospace Studies（多伦多大学航空航天研究所）
School of Computation, Information and Technology (CIT), Technical University of Munich（计算信息与技术学院（CIT），慕尼黑技术大学）；State Key Laboratory for Novel Software Technology and the School of Science and Technology, Nanjing University (Suzhou Campus)（新型软件技术国家重点实验室和南京大学（苏州校区）科学与技术学院）；School of Control Science and Engineering, Shandong University（控制科学与工程学院，山东大学）
Just in time Informed Trees: Manipulability-Aware Asymptotically Optimized Motion Planning
Human-Robot Interfaces and Interaction(HRI2), Istituto Italiano Di Tecnologia (IIT)（人机交互（HRI2），意大利技术研究所（IIT））；Swiss Federal Technology Institute of Lausanne (EPFL)（洛桑联邦理工学院（EPFL））；Technical University of Munich（慕尼黑技术大学）；School of Control Science and Engineering, Shandong University（控制科学与工程学院，山东大学）；School of Computer Science, University of Nottingham, UK（计算机科学学院，诺丁汉大学（英国））
Batch Informed Trees (BIT*): Informed Asymptotically Optimal Anytime Search
Carnegie Mellon University（卡内基梅隆大学）；Massachusetts Institute of Technology（麻省理工学院）；University of Toronto（多伦多大学）；University of Waterloo（滑铁卢大学）；University of Toronto Institute for Aerospace Studies（多伦多大学航空航天研究所）
Learning Spatiotemporal Decision Priors for Efficient Path Planning under Partial Observability
College of Intelligent Robotics and Advanced Manufacturing, Fudan University（智能机器人与先进制造学院，复旦大学）；School of Information Science and Technology, Fudan University（信息科学与技术学院，复旦大学）；Department of Information Technology, Old Dominion University（信息技术系，老 Dominion 大学）
Safe MPC Alignment with Human Directional Feedback
Intelligent Robotics and Interactive Systems (IRIS) Lab in the School for Engineering of Matter, Transport and Energy（智能机器人与交互系统实验室（IRIS））；Polytechnic School（理工学院）；School for Engineering of Matter, Transport and Energy（工程物质、运输与能量学院）；Departments of Industrial Engineering & Management Sciences（工业工程与管理科学系）；Department of Electrical and Systems Engineering（电气与系统工程系）
Department of Computer Science, Rice University（计算机科学系，里士大学）；Department of Computer Science, Purdue University（计算机科学系，普渡大学）；Waymo, LLC（Waymo公司）；Metron, Inc.（Metron公司）；Ken Kennedy Institute at Rice University（里士大学肯尼迪研究所）
