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cs.RO2023★ 1 cited
Neural-Network-Driven Method for Optimal Path Planning via High-Accuracy Region Prediction
Yuan Huang, Cheng-Tien Tsao, Tianyu Shen +1
Sampling-based path planning algorithms suffer from heavy reliance on uniform sampling, which accounts for unreliable and time-consuming performance, especially in complex environm…
cs.RO2023
S&Reg: End-to-End Learning-Based Model for Multi-Goal Path Planning Problem
Yuan Huang, Kairui Gu, Hee-hyol Lee
In this paper, we propose a novel end-to-end approach for solving the multi-goal path planning problem in obstacle environments. Our proposed model, called S&Reg, integrates multi-…
cs.RO2023
PKE-RRT: Efficient Multi-Goal Path Finding Algorithm Driven by Multi-Task Learning Model
Yuan Huang
Multi-goal path finding (MGPF) aims to find a closed and collision-free path to visit a sequence of goals orderly. As a physical travelling salesman problem, an undirected complete…