Autonomous and Safe Navigation of Mobile Robots in Vineyard with Smooth Collision Avoidance

Abhijeet Ravankar, Ankit A. Ravankar, Arpit Rawankar and Yohei Hoshino
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Abhijeet Ravankar: Faculty of Engineering, Kitami Institute of Technology, Kitami 090-8507, Japan
Ankit A. Ravankar: Department of Robotics, Faculty of Engineering, Tohoku University, Sendai 980-8577, Japan
Arpit Rawankar: Department of Electronics and Telecommunication, Vidyalankar Institute of Technology, Mumbai 400037, India
Yohei Hoshino: Faculty of Engineering, Kitami Institute of Technology, Kitami 090-8507, Japan

Agriculture, 2021, vol. 11, issue 10, 1-17

Abstract: In recent years, autonomous robots have extensively been used to automate several vineyard tasks. Autonomous navigation is an indispensable component of such field robots. Autonomous and safe navigation has been well studied in indoor environments and many algorithms have been proposed. However, unlike structured indoor environments, vineyards pose special challenges for robot navigation. Particularly, safe robot navigation is crucial to avoid damaging the grapes. In this regard, we propose an algorithm that enables autonomous and safe robot navigation in vineyards. The proposed algorithm relies on data from a Lidar sensor and does not require a GPS. In addition, the proposed algorithm can avoid dynamic obstacles in the vineyard while smoothing the robot’s trajectories. The curvature of the trajectories can be controlled, keeping a safe distance from both the crop and the dynamic obstacles. We have tested the algorithm in both a simulation and with robots in an actual vineyard. The results show that the robot can safely navigate the lanes of the vineyard and smoothly avoid dynamic obstacles such as moving people without abruptly stopping or executing sharp turns. The algorithm performs in real-time and can easily be integrated into robots deployed in vineyards.

Keywords: vineyard robots; autonomous robots; navigation; feature extraction; collision avoidance (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: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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