Improved localization in a corn crop row using a rotated laser rangefinder for three-dimensional data acquisition
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(2020) 42:592
TECHNICAL PAPER
Improved localization in a corn crop row using a rotated laser rangefinder for three‑dimensional data acquisition Mateus V. Gasparino2 · Vitor A. H. Higuti1 · Andrés E. B. Velasquez2 · Marcelo Becker1 Received: 20 December 2019 / Accepted: 1 October 2020 © The Brazilian Society of Mechanical Sciences and Engineering 2020
Abstract Small robotic vehicles have been navigating agricultural fields in the pursuit of new possibilities to increase agricultural production and to meet the increasing food and energetic demands. However, a perception system with reliable awareness of the surroundings remains a challenge to achieve autonomous navigation. Camera and single-layer laser scanners have been the primary sources of information, yet the first suffers from outdoor light sensibility and both from occlusion by leaves. This paper describes a three-dimensional system acquisition for corn crops. The sensing core is a single-layer UTM30-LX laser scanner rotating around its axis, while an inertial sensor provides angular measurements. With the rotation, multiple layers are used to compose a 3D point cloud, which is represented by a two-dimensional occupancy grid. Each cell is filled according to the number of readings, and their weights derive from two procedures: firstly, a mask enhances vertical entities (stalks); secondly, two Gaussian functions on the expected position of the immediate neighboring rows weaken readings in the middle of the lane and farther rows. The resulting occupancy grid allows the representation of the cornrows by virtual walls, which are used as references to a wall follower algorithm. According to experimental results, the virtual walls are segmented with reduced influence from straying leaves and sparse weeds when compared to the segmentation done with single-layer laser scanner data. Indeed, 64.02% of 3D outputs are within 0.05 m limit error from expected lane width, while only 11.63% of single-layer laser data are within same limit. Keywords Mobile robot · Precision agriculture · Perception · Navigation · LiDAR · 3D Sensor
1 Introduction Agricultural technologies are still in crescent development, which can originate the application of a completely new mechanization method to support the crop management based on small agricultural vehicles. The development and application of small intelligent robots in agriculture allow the supplying of individual plant’s needs, while they can perform operations that were not possible before due to expensive cost or even time-consuming. Technical Editor: Victor Juliano De Negri. * Mateus V. Gasparino [email protected] 1
Mechanical Engineering Department, University of São Paulo, São Carlos, SP, Brazil
Agricultural and Biological Engineering Department, University of Illinois at Urbana-Champaign, Champaign, IL, United States
2
Small vehicles may also have less environmental impact, since they can avoid the over-application of chemicals and fertilizers, requiring lower usage of energy with better control between
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