Approximation algorithms for lawn mowing and milling

By E. Arkin, Sándor P. Fekete, Joseph B. M. Mitchell. Computational geometry, 2000

295 citations recorded by the source corpus.

Subfields: Computer Graphics and Computer-Aided Design, Computer Vision and Pattern Recognition, Industrial and Manufacturing Engineering

View Paper: https://www.semanticscholar.org/paper/f498925210f003f89d392a5588f665b917dcb0d9

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Graphics and Computer-Aided Design

1. M. Carreras
2. Enric Galceran
3. Joseph S. B. Mitchell

In Computer Vision and Pattern Recognition

1. R. Mohd-Mokhtar
2. M. Carreras
3. Enric Galceran
4. Joseph S. B. Mitchell
5. Chee Sheng Tan
6. Mohd Rizal Arshad

In Industrial and Manufacturing Engineering

1. R. Mohd-Mokhtar
2. Joseph S. B. Mitchell
3. Chee Sheng Tan
4. Mohd Rizal Arshad

Citations in the corpus

• Spanning-tree based coverage of continuous areas by a mobile robot (2001, unknown): “[3].”
• A survey on coverage path planning for robotics (2013, background): “Actually, finding a path to cut all the grass of a given region covered by grass, which is known as the " lawnmower problem " , is proven to be NP-hard [Arkin et al., 2000].”
• Geometric Shortest Paths and Network Optimization (2000, methodology): “However, Arkin, Fekete, and Mitchell [24,25] have shown that the problem is NP-hard, even if R is simply connected (e.”
• A Comprehensive Review of Coverage Path Planning in Robotics Using Classical and Heuristic Algorithms (2021, background): “Thus, it introduces a significant challenge to address the CPP problem since TSP and CPP problems are NP-hard [31].”