Path Planning Aware of Robot's Center of Mass for Steep Slope Vineyards

• Type: Article in International Scientific Journal
• Date: 2020

Authors

Luís Santos (Author) Other; Filipe Neves Santos (Author) FEUP; Jorge Mendes (Author) Other; Pedro Gomes da Costa (Author) FEUP; José Lima (Author) Other; Ricardo Reis (Author) Other; Pranjali Shinde (Author) Other

Journal

Title: Robotica

Vol. 38 No. 4

Pages: 684-698

ISSN: 0263-5747

Publisher: Cambridge University Press

Indexing

ISI Web of Knowledge - 31 Citations

Scopus - 34 Citations

Other information

Authenticus ID: P-00Q-SH3

DOI: 10.1017/s0263574719000961

Abstract (EN): Steep slope vineyards are a complex scenario for the development of ground robots. Planning a safe robot trajectory is one of the biggest challenges in this scenario, characterized by irregular surfaces and strong slopes (more than 35 degrees). Moving the robot through a pile of stones, spots with high slope or/and with wrong robot yaw may result in an abrupt fall of the robot, damaging the equipment and centenary vines, and sometimes imposing injuries to humans. This paper presents a novel approach for path planning aware of center of mass of the robot for application in sloppy terrains. Agricultural robotic path planning (AgRobPP) is a framework that considers the A* algorithm by expanding inner functions to deal with three main inputs: multi-layer occupation grid map, altitude map and robot's center of mass. This multi-layer grid map is updated by obstacles taking into account the terrain slope and maximum robot posture. AgRobPP is also extended with algorithms for local trajectory replanning during the execution of a trajectory that is blocked by the presence of an obstacle, always assuring the safety of the re-planned path. AgRobPP has a novel PointCloud translator algorithm called PointCloud to grid map and digital elevation model (PC2GD), which extracts the occupation grid map and digital elevation model from a PointCloud. This can be used in AgRobPP core algorithms and farm management intelligent systems as well. AgRobPP algorithms demonstrate a great performance with the real data acquired from AgRob V16, a robotic platform developed for autonomous navigation in steep slope vineyards.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 15