Rapidly-Exploring Random Trees: Progress and Prospects

  title={Rapidly-Exploring Random Trees: Progress and Prospects},
  author={Steven M. LaValle and James J. Kuffner},

FAR Planner: Fast, Attemptable Route Planner using Dynamic Visibility Update

The method shows the capability to attempt and navigate through unknown environments, reducing travel time by up to 12-47% from search-based methods: A*, D* Lite, and more than 24-35% from sampling- based methods: RRT*, BIT*, and SPARS.

An open‐source system for vision‐based micro‐aerial vehicle mapping, planning, and flight in cluttered environments

We present an open‐source system for Micro‐Aerial Vehicle (MAV) autonomous navigation from vision‐based sensing. Our system focuses on dense mapping, safe local planning, and global trajectory

Path Planning using Multilayer Neural Network and Rapidly-exploring Random Tree

We propose a path generation method that combines a multilayer neural network (MLN) and a rapidlyexploring random tree (RRT), which is a path-planning method that uses random numbers. Specifically,

Concurrent Nearest-Neighbor Searching for Parallel Sampling-Based Motion Planning in SO(3), SE(3), and Euclidean Spaces

This paper presents a fast exact nearest neighbor searching data structure and method that is designed to operate under highly-concurrent parallel operation on modern multi-core processors based on a kd-tree, and demonstrates the proposed method’s performance in a parallelized asymptotically-optimal sampling-based motion planner.

A Partitioning-Based Approach for Robot Path Planning Problems

A Partitioning-Based Path Planning approach, called PBPP, has been proposed by partitioning-based and hierarchical methods that effectively improve the A* algorithm and demonstrates the PBPP’s utility for reducing time-consumption and finding low-cost paths.

A Complete System for Vision-Based Micro-Aerial Vehicle Mapping, Planning, and Flight in Cluttered Environments

A complete system for micro-aerial vehicle autonomous navigation from vision-based sensing using only on-board sensing and processing is presented, and how this map information is best exploited for planning, especially when using narrow field of view sensors in very cluttered environments.

Three-dimensional time-optimal path planning in dynamic and realistic environments

This thesis discusses the theoretical basis of the rigorous partial differential equation based methodology that is utilized in order to plan safe and optimal paths for vehicles with and without motion constraints in three-dimensional dynamic flow-fields and illustrates the working and capabilities of the path planning algorithm by means of a number of applications.

Single-step collision-free trajectory planning of biped climbing robots in spatial trusses

The sampling-based algorithm, Bi-RRT, is utilized to plan single-step collision-free motion for biped climbing robots in spatial trusses to deal with the orientation limit of a 5-DoF biped climb robot.

Viewpoint Planning Framework for Single Guard Robot in Indoor Environment

This thesis describes a global planning algorithm used for the guard robot to continuously and effectively watch a certain object such as a person based on a geodesic motion model and escaping gaps, and exploits the topological features of the environment.

Comparison of motion planning techniques for a multi-rotor UAS equipped with a multi-joint manipulator Arm

This work explains the simulation framework developed and the results obtained with different motion planning methods within this framework and describes the practical interest of this system in situations where it is required to build a structure in places with difficult access by conventional means.