A Comparison of LiDAR-based SLAM Systems for Control of Unmanned Aerial Vehicles

Milijas, Robert; Marković, Lovro; Ivanović, Antun; Petric, Frano; Bogdan, Stjepan

doi:10.1109/icuas51884.2021.9476802

Cited by 30 publications

(17 citation statements)

References 17 publications

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“…The structured indoor farming environment allows us to assume the position of the UAV is accurately measured. For example, this can be achieved using ultra-wideband technology fused together with simultaneous localisation and mapping [6].…”

Section: Aerial Manipulatormentioning

confidence: 99%

Render-in-the-loop aerial robotics simulator: Case Study on Yield Estimation in Indoor Agriculture

Ivanović¹,

Polić²,

Tabak³

et al. 2022

Preprint

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Inspired by recent promising results in sim-toreal transfer in deep learning we built a realistic simulation environment combining a Robot Operating System (ROS)compatible physics simulator (Gazebo) with Cycles, the realistic production rendering engine from Blender. The proposed simulator pipeline allows us to simulate near-realistic RGB-D images. To showcase the capabilities of the simulator pipeline we propose a case study that focuses on indoor robotic farming. We developed a solution for sweet pepper yield estimation task. Our approach to yield estimation starts with aerial robotics control and trajectory planning, combined with deep learningbased pepper detection, and a clustering approach for counting fruit. The results of this case study show that we can combine real time dynamic simulation with near realistic rendering capabilities to simulate complex robotic systems.

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Section: Aerial Manipulatormentioning

confidence: 99%

Render-in-the-loop aerial robotics simulator: Case Study on Yield Estimation in Indoor Agriculture

Ivanović¹,

Polić²,

Tabak³

et al. 2022

Preprint

Self Cite

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“…This approach is facilitated by the underlying mapping and localization stack based on the Cartographer, for which we have shown that localization error and drift are minimal (less than 25 cm) due to loop-closing capabilities of Cartographer, even for a more dynamic robot (UAV), large maps (250 m × 100 m) and large distances covered (more than 600 m), both of which are significantly larger than the arena designated for the ground vehicle in Challenge 2 of MBZIRC2020. For more details on this evaluation, interested reader is invited to read (Milijas et al, 2020). ).…”

Section: Planning and Laying Bricks In The Correct Ordermentioning

confidence: 99%

Autonomous, Mobile Manipulation in a Wall-building Scenario: Team LARICS at MBZIRC 2020

Vatavuk¹,

Polić²,

Hrabar³

et al. 2022

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In this paper we present our hardware design and control approaches for a mobile manipulation platform used in Challenge 2 of the MBZIRC 2020 competition. In this challenge, a team of UAVs and a single UGV collaborate in an autonomous, wall-building scenario, motivated by construction automation and large-scale robotic 3D printing. The robots must be able, autonomously, to detect, manipulate, and transport bricks in an unstructured, outdoor environment. Our control approach is based on a state machine that dictates which controllers are active at each stage of the Challenge. In the first stage our UGV uses visual servoing and local controllers to approach the target object without considering its orientation. The second stage consists of detecting the object’s global pose using OpenCV-based processing of RGB-D image and point-cloud data, and calculating an alignment goal within a global map. The map is built with Google Cartographer and is based on onboard LIDAR, IMU, and GPS data. Motion control in the second stage is realized using the ROS Move Base package with Time-Elastic Band trajectory optimization. Visual servo algorithms guide the vehicle in local object-approach movement and the arm in manipulating bricks. To ensure a stable grasp of the brick’s magnetic patch, we developed a passively-compliant, electromagnetic gripper with tactile feedback. Our fully-autonomous UGV performed well in Challenge 2 and in post-competition evaluations of its brick pick-and-place algorithms.

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“…While their application in autonomous driving is on the rise, their use in aerial robots is still limited because they require more available payload and a more powerful onboard computer than cameras. In [27], a comparison of several algorithms applied to aerial robots is made.…”

Section: Aerial Robots Localizationmentioning

confidence: 99%

Aerial Robotic Solution for Detailed Inspection of Viaducts

et al. 2021

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The inspection of public infrastructure, such as viaducts and bridges, is crucial for their proper maintenance given the heavy use of many of them. Current inspection techniques are very costly and manual, requiring highly qualified personnel and involving many risks. This article presents a novel solution for the detailed inspection of viaducts using aerial robotic platforms. The system provides a highly automated visual inspection platform that does not rely on GPS and could even fly underneath the infrastructure. Unlike commercially available solutions, our system automatically references the inspection to a global coordinate system usable throughout the lifespan of the infrastructure. In addition, the system includes another aerial platform with a robotic arm to make contact inspections of detected defects, thus providing information that cannot be obtained only with images. Both aerial robotic platforms feature flexibility in the choice of camera or contact measurement sensors as the situation requires. The system was validated by performing inspection flights on real viaducts.

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A Comparison of LiDAR-based SLAM Systems for Control of Unmanned Aerial Vehicles

Cited by 30 publications

References 17 publications

Render-in-the-loop aerial robotics simulator: Case Study on Yield Estimation in Indoor Agriculture

Render-in-the-loop aerial robotics simulator: Case Study on Yield Estimation in Indoor Agriculture

Autonomous, Mobile Manipulation in a Wall-building Scenario: Team LARICS at MBZIRC 2020

Aerial Robotic Solution for Detailed Inspection of Viaducts

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