Coverage trajectory planning problem on 3D terrains with safety constraint for automated lawn mower: Exact and heuristic approaches
This repository contains the source code and data for the following paper:
Zhou, H., Zhang, P., Liang, Z., Li, H., & Li, X. (2025). Coverage trajectory planning problem on 3D terrains with safety constraint for automated lawn mower: Exact and heuristic approaches. Robotics and Autonomous Systems..
Autonomous mowing systems offer the potential to enhance efficiency and reduce labor in lawn maintenance. However, the irregularities of real-world terrains such as slopes and obstacles introduce significant safety challenges that must be addressed in trajectory planning. This repository provides the implementation of a trajectory planning framework for automated lawn mowers operating on 3D terrains. It introduces the Coverage Trajectory Planning Problem on 3D Terrains (CTPP-3DT), which jointly optimizes the mower's path and speed profile to minimize completion time while satisfying safety constraints on sloped surfaces. The framework includes a Mixed-Integer Linear Programming model for small-scale instances and a decomposition-based heuristic algorithm using Simulated Annealing for large-scale problems. Benchmark experiments and sensitivity analyses are provided to evaluate the effectiveness and generalizability of the proposed approach.
The project is developed using Java 1.8. Please ensure you have the corresponding environment set up.
The code related to our data processing and algorithm are included in folder src. As you proceed through all code, always verify the paths for both the input and output files. This ensures that everything runs smoothly.
The data folder contains the benchmark reference trajectories used in our paper. You can generate additional instances using src/Main/InstanceGenerator.java.
Each instance is stored as a .txt file with the following format:
map length
map width
(blank line)
obstacle map (0: grass, 1: obstacle, 2: mower start)
(blank line)
height map
Developers - Hang Zhou (hzhou364@wisc.edu).
If you have any questions, please feel free to contact the CATS Lab at UW-Madison. We're here to help!