Position Selection and Collision-Free Path Planning for Fruit Picking Robots
Source abstract
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: crossref · Quality: baseline
Research context
OpenAlex topics: Robotic Path Planning Algorithms · Modular Robots and Swarm Intelligence · Robotics and Sensor-Based Localization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Mechanical Engineering, Hanyang University, Seoul 04763, Republic of Korea
Korea Institute of Industrial Technology (KITECH), Ansan 15588, Republic of Korea
Funding
Ministry of Trade, Industry and Energy (MOTIE) · Korea Institute of Planning and Evaluation for Technology in Food, Agriculture, and Forestry (IPET)
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