Vehicle localization using laser scanner

Szaj, Wiesław; Pieniazek, Jacek

doi:10.1109/metroaerospace48742.2020.9160100

Cited by 2 publications

(1 citation statement)

References 13 publications

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“…To develop the proposed tasks, it is essential to have a good localisation. Conventional methods use GPS [19,20], inertial sensors [21][22][23][24], cameras [25][26][27][28], odometry [29,30], lidars [31][32][33][34][35], kinect [36,37], or combined systems [36,38,39]. Other specific sensors highly used in agriculture are multi-spectral ones, although their application focuses more on the recognition and vegetative analysis than on the location within an environment [40][41][42].…”

Section: Introductionmentioning

confidence: 99%

Robotic Fertilisation Using Localisation Systems Based on Point Clouds in Strip-Cropping Fields

et al. 2020

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The use of robotic systems in organic farming has taken on a leading role in recent years; the Sureveg CORE Organic Cofund ERA-Net project seeks to evaluate the benefits of strip-cropping to produce organic vegetables. This includes, among other objectives, the development of a robotic tool that facilitates the automation of the fertilisation process, allowing the individual treatment (at the plant level). In organic production, the slower nutrient release of the used fertilisers poses additional difficulties, as a tardy detection of deficiencies can no longer be corrected. To improve the detection, as well as counter the additional labour stemming from the strip-cropping configuration, an integrated robotic tool is proposed to detect individual crop deficiencies and react on a single-crop basis. For the development of this proof-of-concept, one of the main objectives of this work is implementing a robust localisation method within the vegetative environment based on point clouds, through the generation of general point cloud maps (G-PC) and local point cloud maps (L-PC) of a crop row. The plants’ geometric characteristics were extracted from the G-PC as a framework in which the robot’s positioning is defined. Through the processing of real-time lidar data, the L-PC is then defined and compared to the predefined reference system previously deduced. Both subsystems are integrated with ROS (Robot Operating System), alongside motion planning, and an inverse kinematics CCD (Cyclic Coordinate Descent) solver, among others. Tests were performed using a simulated environment of the crop row developed in Gazebo, followed by actual measurements in a strip-cropping field. During real-time data-acquisition, the localisation error is reduced from 13 mm to 11 mm within the first 120 cm of measurement. The encountered real-time geometric characteristics were found to coincide with those in the G-PC to an extend of 98.6%.

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Section: Introductionmentioning

confidence: 99%

Robotic Fertilisation Using Localisation Systems Based on Point Clouds in Strip-Cropping Fields

et al. 2020

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Mechatronic Anti-Collision System for Electric Wheelchairs Based on 2D LiDAR Laser Scan

Szaj

Fudali

Wojnarowska

et al. 2021

Sensors

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Electric wheelchairs make it easier for disabled and elderly people to live, move, interact, and participate in society. Moving a wheelchair in open spaces is relatively easy, but in closed and small spaces, maneuvering is difficult. Solutions to such problems for people with disabilities are applicable to a relatively small group of recipients and are mostly custom-made solutions, whose considerable cost is a significant barrier to accessibility. New technologies can provide an opportunity to improve the quality of life of people with disabilities in this aspect. Using selected elements of complex automation and control systems, cost-effective solutions can be created that facilitate the functioning of people with disabilities. This paper presents an analysis of hazards and problems when maneuvering a wheelchair in narrow passageways, as well as the authors’ solution to this problem, and the concept and assumptions of a mechatronic anti-collision system based on 2D LiDAR laser scanners. This solution is composed of a proprietary 2D rotating scanner mechanism that ensures the acquisition of 3D images of the environment around the wheelchair. Preliminary tests of this solution yielded promising results. Further research will include miniaturization of the device.

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Vehicle localization using laser scanner

Cited by 2 publications

References 13 publications

Robotic Fertilisation Using Localisation Systems Based on Point Clouds in Strip-Cropping Fields

Robotic Fertilisation Using Localisation Systems Based on Point Clouds in Strip-Cropping Fields

Mechatronic Anti-Collision System for Electric Wheelchairs Based on 2D LiDAR Laser Scan

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