3 accepted papers
This work proposes a fast algorithm for scheduling and trajectory planning of multiple Cartesian robotic arms harvesting fruits in an orchard row segment. The algorithm partitions the workspace adaptively along the segment, computes tight and feasible fruit-picking schedules and vehicle travel speed
Autonomous agricultural vehicles (AAVs), including field robots and autonomous tractors, are becoming essential in modern farming by improving efficiency and reducing labor costs. A critical task in AAV operations is headland turning between crop rows. This task is challenging in orchards with limit
Plant factory cultivation is widely recognized for its ability to optimize resource use and boost crop yields. To further increase the efficiency in these environments, we propose a mixed-integer linear programming (MILP) framework that systematically schedules and coordinates dual-arm harvesting ta