Monocular Visual Mapping for Obstacle Avoidance on UAVs

Magree, Daniel; Mooney, John G.; Johnson, Eric N.

doi:10.1007/s10846-013-9967-7

Cited by 26 publications

(15 citation statements)

References 13 publications

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“…In order to implement a suitable attitude controller for the drone prototype, an accurate dynamic model needs to be developed [21]. This model is based on certain assumptions, in order to simplify the dynamics of that complex system, so as to be suitable for simulation.…”

Section: Dynamic Modelling Of Hexa-rotor Dronementioning

confidence: 99%

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Navigation and Applicability of Hexa Rotor Drones in Greenhouse Environment

Šimon

Petkovic

et al. 2018

Teh. vjesn.

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The paper discusses use-cases and a broad description of application possibilities of drones in greenhouses. Unmanned autonomous aerial vehicles (UAV), i.e. drones, are being used increasingly often for the direct or indirect collection of data. GPS navigation cannot be applied in an indoor work environment. One of the alternatives is to measure the distance from a fixed set of sensors with known positions. The paper presents a dynamic model for a hexa-rotor drone. In order to ensure reliable navigation a new navigation algorithm is presented based on the two-dimensional navigation algorithm of the robot motion control. It demonstrates the development of a threedimensional navigation algorithm for the hexa-rotor drone with the hypothesis that the elaborate three-dimensional model can navigate the drone in an indoor environment. To prove the hypothesis, the simulation is implemented in Scilab environment with information about the flight path deviation from the planned routes, which is also given in the work.

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Section: Dynamic Modelling Of Hexa-rotor Dronementioning

confidence: 99%

“…This work introduces a new technique for finding indoor 3D location of a drone by using Received Signal Strength Indication (RSSI) [21,22,24]. The proposed localization algorithm is derived from multilateration algorithm with composition of empirical path loss model.…”

Section: D Navigation Algorithmmentioning

confidence: 99%

Navigation and Applicability of Hexa Rotor Drones in Greenhouse Environment

Šimon

Petkovic

et al. 2018

Teh. vjesn.

View full text Add to dashboard Cite

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“…Because of the limited payload of MAVs, most approaches to obstacle avoidance are camera based (Mori & Scherer, ; Ross et al., ; Schmid, Lutz, Tomic, Mair, & Hirschmüller, ; Magree, Mooney, & Johnson, ; Tripathi, G Raja, & Padhi, ; Flores, Zhou, Lozano, & Castillo, ; Schauwecker & Zell, ; Park & Kim, ). Approaches using monocular cameras to detect obstacles require movement in order to perceive the same surface points from different perspectives for being able to triangulate depth.…”

Section: Related Workmentioning

confidence: 99%

Multilayered Mapping and Navigation for Autonomous Micro Aerial Vehicles

Droeschel

Nieuwenhuisen

Beul

et al. 2015

Journal of Field Robotics

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Micro aerial vehicles, such as multirotors, are particularly well suited for the autonomous monitoring, inspection, and surveillance of buildings, e.g., for maintenance or disaster management. Key prerequisites for the fully autonomous operation of micro aerial vehicles are real-time obstacle detection and planning of collision-free trajectories. In this article, we propose a complete system with a multimodal sensor setup for omnidirectional obstacle perception consisting of a three-dimensional (3D) laser scanner, two stereo camera pairs, and ultrasonic distance sensors. Detected obstacles are aggregated in egocentric local multiresolution grid maps. Local maps are efficiently merged in order to simultaneously build global maps of the environment and localize in these. For autonomous navigation, we generate trajectories in a multilayered approach: from mission planning over global and local trajectory planning to reactive obstacle avoidance. We evaluate our approach and the involved components in simulation and with the real autonomous micro aerial vehicle. Finally, we present the results of a complete mission for autonomously mapping a building and its surroundings. C 2015 Wiley Periodicals, Inc.

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“…State-of-the art obstacle-avoidance systems have their basis in either vision-aided techniques (19)(20)(21)(22)(23)(24)(25)(26)(27), such as optical flow (28)(29)(30), or distance sensors exploiting radar (31,32), lidar (33), and sonar (34)(35)(36) technologies. A widely used obstacle detection and avoidance method is simultaneous localization and mapping, which builds an accurate map of obstacles by using high-precision onboard sensors (37)(38)(39)(40)(41)(42)(43)(44). Other effectively demonstrated methods include collision-recovering controllers along with simple motion planners, enabling robots to navigate without complete knowledge of their surroundings.…”

Section: Introductionmentioning

confidence: 99%

Rotorigami: A rotary origami protective system for robotic rotorcraft

et al. 2018

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Applications of aerial robots are progressively expanding into complex urban and natural environments. Despite remarkable advancements in the field, robotic rotorcraft is still drastically limited by the environment in which they operate. Obstacle detection and avoidance systems have functionality limitations and substantially add to the computational complexity of the onboard equipment of flying vehicles. Furthermore, they often cannot identify difficult-to-detect obstacles such as windows and wires. Robustness to physical contact with the environment is essential to mitigate these limitations and continue mission completion. However, many current mechanical impact protection concepts are either not sufficiently effective or too heavy and cumbersome, severely limiting the flight time and the capability of flying in constrained and narrow spaces. Therefore, novel impact protection systems are needed to enable flying robots to navigate in confined or heavily cluttered environments easily, safely, and efficiently while minimizing the performance penalty caused by the protection method. Here, we report the development of a protection system for robotic rotorcraft consisting of a free-to-spin circular protector that is able to decouple impact yawing moments from the vehicle, combined with a cyclic origami impact cushion capable of reducing the peak impact force experienced by the vehicle. Experimental results using a sensor-equipped miniature quadrotor demonstrated the impact resilience effectiveness of the Rotary Origami Protective System (Rotorigami) for a variety of collision scenarios. We anticipate this work to be a starting point for the exploitation of origami structures in the passive or active impact protection of robotic vehicles.

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Monocular Visual Mapping for Obstacle Avoidance on UAVs

Cited by 26 publications

References 13 publications

Navigation and Applicability of Hexa Rotor Drones in Greenhouse Environment

Navigation and Applicability of Hexa Rotor Drones in Greenhouse Environment

Multilayered Mapping and Navigation for Autonomous Micro Aerial Vehicles

Rotorigami: A rotary origami protective system for robotic rotorcraft

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