Heuristic approaches in robot path planning: A survey
By Thi Thoa Mac, Cosmin Copot, Trung Tran Duc, Robin M. C. De Keyser. Robotics Auton. Syst., 2016
599 citations recorded by the source corpus.
Subfields: Aerospace Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/fa7a23a37dd8cffaac686eb26feb7a1e8886962d
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Aerospace Engineering
- S. Gadre
- Alfonso J. García-Cerezo
- Carlos Jesús Pérez-del-Pulgar
- J. Sánchez-Ibáñez
- Ludwig Schmidt
- Gabriel Ilharco
- Shuran Song
- Mitchell Wortsman
In Computer Vision and Pattern Recognition
- Ludwig Schmidt
- Gabriel Ilharco
- Mitchell Wortsman
- S. Gadre
- Shuran Song
- Luc Van Gool
- Ming-Hsuan Yang
- Jitendra Malik
In Control and Systems Engineering
- S. Gadre
- Alfonso J. García-Cerezo
- Carlos Jesús Pérez-del-Pulgar
- J. Sánchez-Ibáñez
- Shuran Song
- Bo Li
- Andy Zeng
Citations in the corpus
- CLIP on Wheels: Zero-Shot Object Navigation as Object Localization and Exploration (2022, background): “While these frameworks are used widely for different robotics applications [21], they are known to be fragile in the presence of uncertainty [41].”
- Path Planning for Autonomous Mobile Robots: A Review (2021, methodology): “Further insights and a more extensive surveys on related hybrid methods are provided in Mac et al. [8].”
- Geometric A-Star Algorithm: An Improved A-Star Algorithm for AGV Path Planning in a Port Environment (2021, background): “The focus of a path planning is to build a reasonable obstacle distribution map based on the known environment [7], and then find a path with the least cost to avoid obstacles [8].”