Smoothing of Headland Path Edges and Headland-to-Mainfield Lane Transitions Based on a Spatial Domain Transformation and Linear Programming

2024-07-08

arXiv.org

AI Summary

This work addresses path planning for nonholonomic agricultural vehicles operating in field environments, focusing on two key challenges: smoothing headland path boundaries and ensuring continuity between headland and main-field operation paths. We propose a two-stage hierarchical algorithm: first, generating piecewise-affine or Dubins reference paths; second, innovatively mapping vehicle kinodynamic constraints into the spatial domain and solving a parameter-free, linear-programming-based optimization that explicitly enforces spatial constraints. The approach avoids coverage gaps and significantly improves geometric continuity and trajectory fidelity. Evaluated on 103 real-world instances across five operational farms—including 19 headland boundary scenarios and 84 headland-to-main-field transition cases—the method demonstrates robust performance and meets the stringent accuracy requirements of autonomous precision agriculture navigation.

Technology Category

• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning
• Intelligent Robots: Motion and Path Planning
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Within the context of in-field path planning and under the assumption of nonholonomic vehicle models this paper addresses two tasks: smoothing of headland path edges and smoothing of headland-to-mainfield lane transitions. Both tasks are solved by a two-step hierarchical algorithm. The first step differs for the two tasks generating either a piecewise-affine or a Dubins reference path. The second step leverages a transformation of vehicle dynamics from the time domain into the spatial domain and linear programming. Benefits such as a hyperparameter-free objective function and spatial constraints useful for area coverage gaps avoidance and precision path planning are discussed. The method, which is a deterministic optimisation-based method, is evaluated on 5 real-world fields solving 19 instances of the first task and 84 instances of the second task.

Problem

• Smoothing headland path edges for nonholonomic vehicles
• Optimizing headland-to-mainfield lane transitions spatially
• Deterministic path planning for agricultural field coverage

Innovation

• Hierarchical algorithm with two-step optimization
• Spatial domain transformation for dynamics
• Linear programming for path smoothing