ArticleFrontiers in plant science2024
Improving path planning for mobile robots in complex orchard environments: the continuous bidirectional Quick-RRT* algorithm.
Article in Frontiers in plant science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed.
- Agricultural Cyber-Physical Systems: Research Progress in Perception-Driven Multi-Robot Coordination and Logistics in Unstructured Environments.Sensors (Basel, Switzerland) · 2026Review
- Perception and Localization Error Propagation and Robust Path-Tracking Control for Agricultural Machinery in Hilly Orchards: A Review.Sensors (Basel, Switzerland) · 2026Review
- Path planning for volumetric flask grasping based on visual guidance and multi-constraint optimization.PloS one · 2026Article
- Accelerating RRT* convergence with novel nonuniform and uniform sampling approach.Scientific reports · 2025Article
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Authors and funding
3 authors.
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Abstract
Efficient obstacle-avoidance path planning is critical for orchards with numerous irregular obstacles. This paper presents a continuous bidirectional Quick-RRT* (CBQ-RRT*) algorithm based on the bidirectional RRT (Bi-RRT) and Quick-RRT* algorithms and proposes an expansion cost function that evaluates path smoothness and length to overcome the limitations of the Quick-RRT* algorithm for non-holonomic mobile robot applications. To improve the zigzag between dual trees caused by the dual-tree expansion of the Bi-RRT algorithm, CBQ-RRT* proposes the CreateConnectNode optimization method, which effectively solves the path smoothness problem at the junction of dual trees. Simulations conducted on the ROS platform showed that the CBQ-RRT* outperformed the unidirectional Quick-RRT* in terms of efficiency for various orchard layouts and terrain conditions. Compared to Bi-RRT*, CBQ-RRT* reduced the average path length and maximum heading angle by 8.5% and 21.7%, respectively. In addition, field tests confirmed the superior performance of the CBQ-RRT*, as evidenced by an average maximum path lateral error of 0.334 m, a significant improvement over Bi-RRT* and Quick-RRT*. These improvements demonstrate the effectiveness of the CBQ-RRT* in complex orchard environments.
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