An Integrated Route and Path Planning Strategy for Skid–Steer Mobile Robots in Assisted Harvesting Tasks with Terrain Traversability Constraints

Ricardo Paul Urvina, César Leonardo Guevara, Juan Pablo Vásconez and Alvaro Javier Prado ()
Additional contact information
Ricardo Paul Urvina: Departamento de Ingeniería de Sistemas y Computación, Universidad Católica del Norte, Antofagasta 1249004, Chile
César Leonardo Guevara: Lincoln Institute for Agri-Food Technology, University of Lincoln, Lincoln LN2 2LG, UK
Juan Pablo Vásconez: Energy Transformation Center, Faculty of Engineering, Universidad Andrés Bello, Santiago 7500000, Chile
Alvaro Javier Prado: Departamento de Ingeniería de Sistemas y Computación, Universidad Católica del Norte, Antofagasta 1249004, Chile

Agriculture, 2024, vol. 14, issue 8, 1-26

Abstract: This article presents a combined route and path planning strategy to guide Skid–Steer Mobile Robots (SSMRs) in scheduled harvest tasks within expansive crop rows with complex terrain conditions. The proposed strategy integrates: (i) a global planning algorithm based on the Traveling Salesman Problem under the Capacitated Vehicle Routing approach and Optimization Routing (OR-tools from Google) to prioritize harvesting positions by minimum path length, unexplored harvest points, and vehicle payload capacity; and (ii) a local planning strategy using Informed Rapidly-exploring Random Tree ( IRRT * ) to coordinate scheduled harvesting points while avoiding low-traction terrain obstacles. The global approach generates an ordered queue of harvesting locations, maximizing the crop yield in a workspace map. In the second stage, the IRRT * planner avoids potential obstacles, including farm layout and slippery terrain. The path planning scheme incorporates a traversability model and a motion model of SSMRs to meet kinematic constraints. Experimental results in a generic fruit orchard demonstrate the effectiveness of the proposed strategy. In particular, the IRRT * algorithm outperformed RRT and RRT * with 96.1% and 97.6% smoother paths, respectively. The IRRT * also showed improved navigation efficiency, avoiding obstacles and slippage zones, making it suitable for precision agriculture.

Keywords: route and path planning; traveling salesman problem; rapidly-exploring random tree; capacitated vehicle routing; skid–steer mobile robot; harvesting tasks; terrain traversability constraints; agricultural machinery (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2077-0472/14/8/1206/pdf (application/pdf)
https://www.mdpi.com/2077-0472/14/8/1206/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jagris:v:14:y:2024:i:8:p:1206-:d:1440818

Access Statistics for this article

Agriculture is currently edited by Ms. Leda Xuan

More articles in Agriculture from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().