Work

Position Selection and Collision-Free Path Planning for Fruit Picking Robots

Year: 2025

Type: article

Abstract: As the population continues to grow, the need for increased food production has become increasingly evident. However, the agricultural workforce is decreasing due to industrialization. To address this gap, numerous research efforts are underway to adopt robots for harvesting. While significant progress has been made, especially in fruit harvesting using robotic systems, there are still inefficiencies and areas where human intervention is necessary. This paper proposes an algorithm for selecting the position of a mobile manipulator for fruit harvesting using an inverse reachability map to achieve automation and enhance efficiency. Additionally, a method for collision-free path planning in joint space using the model predictive artificial potential field (MPAPF) algorithm is proposed. The effectiveness of the proposed position selection and path planning algorithms was validated through harvesting simulations and a collision-free path was validated in experiments.

Source: Applied Sciences

DOI: 10.3390/app15084419

Authors: Yonghee Cho, Dongwoon Choi, Kwangeun Ko, Jong Hyeon Park

Institutions: Hanyang University, Korea Institute of Industrial Technology

Language: English

Topic: Robotic Path Planning Algorithms

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,896

Funders: Ministry of Trade, Industry and Energy, Ministry of Agriculture, Food and Rural Affairs, Korea Evaluation Institute of Industrial Technology, Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry