iA $^$ : Imperative Learning-based A $^$ Search for Path Planning

23 March 2024

Papers citing "iA$^$: Imperative Learning-based A$^$ Search for Path Planning"

8 / 8 papers shown

Title
Autonomous Exploration Development Environment and the Planning Algorithms Chao Cao H. Zhu Fan Yang Yukun Xia Howie Choset Jean Oh Ji Zhang 45 81 0 27 Oct 2021
Path Planning using Neural A* Search Ryo Yonetani Tatsunori Taniai M. Barekatain Mai Nishimura Asako Kanezaki 3DPC 77 96 0 16 Sep 2020
Adaptively Informed Trees (AIT*): Fast Asymptotically Optimal Path Planning through Adaptive Heuristics Marlin P. Strub Jonathan Gammell 50 82 0 16 Feb 2020
Motion Planning Networks: Bridging the Gap Between Learning-based and Classical Motion Planners A. H. Qureshi Yinglong Miao Anthony Simeonov Michael C. Yip PINN 3DV 74 216 0 13 Jul 2019
Data-driven Planning via Imitation Learning Sanjiban Choudhury M. Bhardwaj S. Arora Ashish Kapoor G. Ranade Sebastian Scherer Debadeepta Dey 73 81 0 17 Nov 2017
Matterport3D: Learning from RGB-D Data in Indoor Environments Angel X. Chang Angela Dai Thomas Funkhouser Maciej Halber Matthias Nießner Manolis Savva Shuran Song Andy Zeng Yinda Zhang 3DV 3DPC 157 1,893 0 18 Sep 2017
Informed RRT*: Optimal Sampling-based Path Planning Focused via Direct Sampling of an Admissible Ellipsoidal Heuristic Jonathan Gammell S. Srinivasa Timothy D. Barfoot 60 834 0 08 Apr 2014
Sampling-based Algorithms for Optimal Motion Planning S. Karaman Emilio Frazzoli 94 4,675 0 05 May 2011