Year: 2026
Type: article
Abstract: Considering the complex terrain of gobi orchards, including irrigation-induced orchard ditches and unstructured environments caused by low-hanging branches of spindle-shaped fruit trees, an improved A*-based regional path planning method is pro-posed for gobi orchards. First, penalty terms based on the distances to the orchard ditch centerline and edge were introduced during path searching. These terms provide adaptive constraints that guide the planned path toward the central region between fruit tree rows, effectively preventing the path from approaching orchard ditches and low-hanging branches. Second, to address the large spatial extent and high computational complexity of Gobi orchard environments, a semicircular arc search strategy was incorporated into the improved A* algorithm to enhance computational efficiency.Finally, the initial path was smoothed using a minimum turning radius circle and a dynamically adjusted two-line tangent strategy. This process generates a globally feasible path with continuous tangency, no sharp turning angles, compliance with the minimum turning radius constraint, and safe executability.The MATLAB simulation results showed that, compared with the conventional A* algorithm, the improved A* algorithm reduced the planning time and the number of searched nodes by 19.43% and 49.1%, respectively, while increasing the path length by 16.9%. Field test results showed that, although the overall path length increased, the improved A* algorithm exhibited high stability across repeated experiments and generated smoother paths. Therefore, the proposed method improves planning efficiency while generating safe and reliable paths under complex road conditions in gobi orchard environments.
Source: Frontiers in Robotics and AI
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,353
OpenAlex ID: W7225662460