Path Planning for Coverage Spraying of Plants in Outdoor Wheeled Mobile Robots

In contemporary agricultural practices and pest management, the deployment of outdoor wheeled mobile robots for precise and efficient plant spraying is crucial to optimize chemical application and mitigate environmental impact. This study introduces an integrated path planning framework designed to systematically tackle the challenges of obstacle avoidance, adherence to kinematic constraints, and optimization of spraying operations, while ensuring complete coverage of target plants. The framework comprises three key components: a local route generator utilizing principal component analysis to minimize movement required for spraying, thereby enhancing efficiency; a global path optimizer that effectively sequences and connects the generated routes to produce collision-free paths; and a path regulator that fine-tunes the resulting paths to comply with the robot's kinematic constraints. Extensive simulations across various outdoor scenarios demonstrate that the proposed framework achieves comprehensive coverage, reduces path lengths, and improves operational efficiency, presenting a viable solution for advanced robotic spraying applications.