SmartCaveDrone: 3D cave mapping using UAVs as robotic co-archaeologists

Zhang, Guoxiang; Shang, Bo; Chen, YangQuan; Moyes, Holley

doi:10.1109/icuas.2017.7991499

Cited by 26 publications

(24 citation statements)

References 31 publications

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“…Active stereo techniques project a set of distinct features onto the surface. The active stereo camera is combined with an Inertial Measurement Unit (IMU) for effective localization in the context of drone-based 3D cave mapping [ 63 ]. A similar approach is found in [ 51 ] for mapping of underground tunnels.…”

Section: Related Workmentioning

confidence: 99%

3D Sensors for Sewer Inspection: A Quantitative Review and Analysis

Bahnsen

Johansen

Philipsen

et al. 2021

Sensors

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Automating inspection of critical infrastructure such as sewer systems will help utilities optimize maintenance and replacement schedules. The current inspection process consists of manual reviews of video as an operator controls a sewer inspection vehicle remotely. The process is slow, labor-intensive, and expensive and presents a huge potential for automation. With this work, we address a central component of the next generation of robotic inspection of sewers, namely the choice of 3D sensing technology. We investigate three prominent techniques for 3D vision: passive stereo, active stereo, and time-of-flight (ToF). The Realsense D435 camera is chosen as the representative of the first two techniques wheres the PMD CamBoard pico flexx represents ToF. The 3D reconstruction performance of the sensors is assessed in both a laboratory setup and in an outdoor above-ground setup. The acquired point clouds from the sensors are compared with reference 3D models using the cloud-to-mesh metric. The reconstruction performance of the sensors is tested with respect to different illuminance levels and different levels of water in the pipes. The results of the tests show that the ToF-based point cloud from the pico flexx is superior to the output of the active and passive stereo cameras.

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Section: Related Workmentioning

confidence: 99%

3D Sensors for Sewer Inspection: A Quantitative Review and Analysis

Bahnsen

Johansen

Philipsen

et al. 2021

Sensors

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“…The papers that were published prior to 2015 were dropped. The resulting list contained 17 papers [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19], which were filtered by excluding papers that did not comply to at least one of the following requirements: Due to the formulation of the problem task, reviewed papers should be characterized by a set of unified criteria that describe how the main challenges are handled. These criteria can be structured in a form of five questions for each paper:…”

Section: State Of the Artmentioning

confidence: 99%

“…Systems of a homogeneous architecture (i.e., all drones have the same role) with a centralized control are the most common among all reviewed articles [3,9,10,[13][14][15]. A big subset of these solutions [9,10,13,14] organize control by a similar scheme-all drones capture images and/or videos using a predefined set or independent trajectories [9,14], set of predefined waypoints [10] or moving in a stable formation by a single predefined trajectory [13].…”

Section: What Multiagent Approach Is Used?mentioning

confidence: 99%

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Multi-Drone 3D Building Reconstruction Method

2021

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In the recent decade, the rapid development of drone technologies has made many spatial problems easier to solve, including the problem of 3D reconstruction of large objects. A review of existing solutions has shown that most of the works lack the autonomy of drones because of nonscalable mapping techniques. This paper presents a method for centralized multi-drone 3D reconstruction, which allows performing a data capturing process autonomously and requires drones equipped only with an RGB camera. The essence of the method is a multiagent approach—the control center performs the workload distribution evenly and independently for all drones, allowing simultaneous flights without a high risk of collision. The center continuously receives RGB data from drones and performs each drone localization (using visual odometry estimations) and rough online mapping of the environment (using image descriptors for estimating the distance to the building). The method relies on a set of several user-defined parameters, which allows the tuning of the method for different task-specific requirements such as the number of drones, 3D model detalization, data capturing time, and energy consumption. By numerical experiments, it is shown that method parameters can be estimated by performing a set of computations requiring characteristics of drones and the building that are simple to obtain. Method performance was evaluated by an experiment with virtual building and emulated drone sensors. Experimental evaluation showed that the precision of the chosen algorithms for online localization and mapping is enough to perform simultaneous flights and the amount of captured RGB data is enough for further reconstruction.

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“…In addition, their approach requires substantial computing power using a Raspberry Pi 3b. Similarly, Zhang et al [ 20 ] proposed a method for 3D cave mapping for archaeology applications using a drone. Their proposed drone is intended for use with human support for controlling it, and thus cannot be seen as a fully autonomous drone.…”

Section: Introductionmentioning

confidence: 99%

Vision-Less Sensing for Autonomous Micro-Drones

Pikalov

Azaria

Sonnenberg

et al. 2021

Sensors

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This work presents a concept of intelligent vision-less micro-drones, which are motivated by flying animals such as insects, birds, and bats. The presented micro-drone (named BAT: Blind Autonomous Tiny-drone) can perform bio-inspired complex tasks without the use of cameras. The BAT uses LIDARs and self-emitted optical-flow in order to perform obstacle avoiding and maze-solving. The controlling algorithms were implemented on an onboard micro-controller, allowing the BAT to be fully autonomous. We further present a method for using the information collected by the drone to generate a detailed mapping of the environment. A complete model of the BAT was implemented and tested using several scenarios both in simulation and field experiments, in which it was able to explore and map complex building autonomously even in total darkness.

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SmartCaveDrone: 3D cave mapping using UAVs as robotic co-archaeologists

Cited by 26 publications

References 31 publications

3D Sensors for Sewer Inspection: A Quantitative Review and Analysis

3D Sensors for Sewer Inspection: A Quantitative Review and Analysis

Multi-Drone 3D Building Reconstruction Method

Vision-Less Sensing for Autonomous Micro-Drones

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