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Optimization of sampling structure on unmanned aerial vehicle for gas leakage monitoring in the atmosphere

ROBOTICA 2024年

作者： Ma, Denglong Guo, Sicheng Zhou, Yuxiang Xi An Jiao Tong Univ Sch Mech Engn Xian Shaanxi Peoples R China Xi An Jiao Tong Univ State Key Lab Mfg Syst Engn Xian Shaanxi Peoples R China

In order to make a fast and accurate response to gas leakage event, e.g. gas leakage in hydrogen storage station, it is very important to identify and locate the leakage source accurately and quickly. Due to the flexibility and the adaptability of robots to harsh environments, leakage source tracing based on mobile robots has attracted more and more attention. However, the existing ground robots are limited by the ground environment and thus it is difficult to trace and locate the leakage in the complex environment with ground robots. Although unmanned aerial vehicle (UAV) can overcome the limitation of ground obstacles, there are still some problems in the accuracy and reliability of gas sampling due to the interference of flow field caused by UAV rotors to the surrounding gases. Based on computational fluid dynamic simulation, a simulation model of UAV with four rotors was established. Combined with test experiments, the influence of flow field around UAV on gas sampling under different UAV speeds, rotors assembly structures, leakage, and sampling conditions was analyzed and investigated. The optimized UAV assembly structure and gas sensor installation position were determined and verified by the simulations and experiments. The results showed that the sensor was less affected by the rotor airflow when the UAV rotor was reversely assembled and the gases were sampled above the UAV. This research can provide a guidance for gas sampling for emission source tracing with UAV for process safety management of energy gas storage.

关键词： aerial robotics mobile robots design computational fluid dynamic simulation robot localization sensor or actuator design

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Vision techniques for on-board detection, following, and mapping of moving targets

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JOURNAL OF FIELD robotics 2019年第1期36卷 252-269页

作者： Stepan, Petr Krajnik, Tomas Petrlik, Matej Saska, Martin Czech Tech Univ Dept Cybernet Prague 16627 Czech Republic Czech Tech Univ Dept Comp Sci Prague Czech Republic

This study presents computer vision modules of a multi-unmanned aerial vehicle (UAV) system, which scored gold, silver, and bronze medals at the Mohamed Bin Zayed International robotics Challenge 2017. This autonomous system, which was running completely on board and in real time, had to address two complex tasks in challenging outdoor conditions. In the first task, an autonomous UAV had to find, track, and land on a human-driven car moving at 15 km/hr on a figure-eight-shaped track. During the second task, a group of three UAVs had to find small colored objects in a wide area, pick them up, and deliver them into a specified drop-off zone. The computer vision modules presented here achieved computationally efficient detection, accurate localization, robust velocity estimation, and reliable future position prediction of both the colored objects and the car. These properties had to be achieved in adverse outdoor environments with changing light conditions. Lighting varied from intense direct sunlight with sharp shadows cast over the objects by the UAV itself, to reduced visibility caused by overcast to dust and sand in the air. The results presented in this paper demonstrate good performance of the modules both during testing, which took place in the harsh desert environment of the central area of United Arab Emirates, as well as during the contest, which took place at a racing complex in the urban, near-sea location of Abu Dhabi. The stability and reliability of these modules contributed to the overall result of the contest, where our multi-UAV system outperformed teams from world's leading robotic laboratories in two challenging scenarios.

关键词： aerial robotics cooperative robots mapping sensors

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Image-Based Control for aerial Manipulation

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ASIAN JOURNAL OF CONTROL 2014年第3期16卷 646-656页

作者： Mebarki, Rafik Lippiello, Vincenzo Univ Naples Federico II Dept Elect Engn & Informat Technol PRISMA Lab I-80125 Naples Italy

This paper presents a new image-based servo control scheme that endows an unmanned aerial vehicle (UAV) equipped with a robotic arm with the capability of automatically positioning elements on target objects. Through a new formalism, the proposed visual servo scheme controls both the UAV and the manipulator simultaneously. It takes into account the whole system redundancy as well as the peculiarity of under-actuation related to rotary-wing crafts. While it controls the system at the velocity level, it makes use of the mobility afforded by the UAV and the dexterity inherent to robot manipulators. The case of large initial errors is explicitly addressed. Results of simulations are reported to verify the effectiveness of the proposed approach.

关键词： visual servoing aerial manipulation aerial robotics

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DEEP-PEST-DETECTOR: AUTOMATED DETECTION AND LOCALIZATION OF PROCESSIONARY MOTH NESTS ON PINE TREES VIA aerial DRONES AND DEEP NEURAL NETWORKS

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APPLIED ENGINEERING IN AGRICULTURE 2022年第2期38卷 253-271页

作者： Jaber, Nael Daher, Naseem Asmar, Daniel Amer Univ Beirut Beirut Lebanon

The pine processionary moth (PPM) is considered the main defoliator of pine trees and is a menacing threat to various other perennial species including oak and cedar. Given their negative secondary effects, spraying of pesticides has been banned as a means for the eradication of PPM;instead, an individualized approach is to be adopted, in which each nest is localized and destroyed. Detection of PPM nests using optical sensing is challenging because of the changing outdoor lighting conditions and the camouflaged appearance of moth in the underlying foliage. This article proposes a promising solution for nest detection by fusing sensory data from an RGB camera on one hand, and a thermal camera on the other, both mounted on an aerial drone. The proposed detection system is built on a two-channeled deep convolutional neural network, one for each spectrum of the collected sensory data. Experiments performed in a pine forest demonstrate successful detection rates with an average accuracy of 97% in various experiments and settings. Geo-localization is performed to report the position of the detected nests within a scanned forest map by means of an estimation scheme that is particularly designed for this purpose achieving centimeter accuracy (<20 cm).

关键词： aerial robotics Agriculture Detection Machine learning Multi-stream CNN Pest control

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Globally Asymptotically Stable Sensor-Based Simultaneous Localization and Mapping

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IEEE TRANSACTIONS ON robotics 2013年第6期29卷 1380-1395页

作者： Guerreiro, Bruno J. N. Batista, Pedro Silvestre, Carlos Oliveira, Paulo Univ Tecn Lisboa Inst Super Tecn Inst Syst & Robot P-1049001 Lisbon Portugal Univ Macau Fac Sci & Technol Taipa Peoples R China

This paper presents the design, analysis, and experimental validation of a globally asymptotically stable (GAS) filter for simultaneous localization and mapping (SLAM), with application to unmanned aerial vehicles. The SLAM problem is formulated in a sensor-based framework and modified in such a way that the underlying system structure can be regarded as linear time varying for observability analysis and filter design purposes, from which a linear Kalman filter with GAS error dynamics follows naturally. The performance and consistency validation of the proposed sensor-based SLAM filter are successfully assessed with real data, acquired indoors, using an instrumented quadrotor.

关键词： aerial robotics globally asymptotically stable (GAS) mapping sensor fusion simultaneous localization and mapping (SLAM)

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Communication Delay in UAV Missions: A Controller Gain Analysis to Improve Flight Stability

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IEEE LATIN AMERICA TRANSACTIONS 2023年第1期21卷 7-15页

作者： Fagundes-Junior, Leonardo A. Coelho, Andre F. Villa, Daniel K. D. Sarcinelli-Filho, Mario Brandao, Alexandre S. Univ Fed Vicosa Nucleo Especializacao Robot Dept Elect Engn Vicosa MG Brazil Univ Fed Vicosa Grad Program Comp Sci Vicosa MG Brazil German Aerosp Ctr DLR Inst Robot & Mechatron Wessling Germany Univ Fed Espirito Santo Dept Elect Engn Grad Program Elect Engn Vitoria ES Brazil

In real-world applications involving unmanned aerial vehicles (UAVs) the presence of communication delays can deteriorate the performance of flight control system or even cause instabilities. However, it is possible to improve the performance and ensure flight stability in the task execution by properly controlling the UAV considering the transport delay. This work analyzes the asymptotic convergence of a quadrotor, under time-delay in the communication with a ground control station. The effects of the communication delay, as well as the response-signal behavior of the quadrotors in the accomplishment of positioning missions are presented and analyzed by numerical simulations. The performance indexes (IAE and ITAE) assist the estimation of the acceptable time-delay limit. The results show that the adopted controller, without any adaptive tuning, can handle a delay of up to 1.2 seconds, which means a blind time of 40 packets of information. As expected, the longer the delay, the lower the gains. Consequently, as the delay increases, the quadrotor takes longer to accomplish the mission carefully and successfully.

关键词： Time-Delayed Control Gain-schedule Analysis Performance Indexes Communication Delay aerial robotics

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Aggressive flight of fixed-wing and quadrotor aircraft in dense indoor environments

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2015年第7期34卷 969-1002页

作者： Bry, Adam Richter, Charles Bachrach, Abraham Roy, Nicholas MIT Comp Sci & Artificial Intelligence Lab Cambridge MA 02139 USA

In this paper, we describe trajectory planning and state estimation algorithms for aggressive flight of micro aerial vehicles in known, obstacle-dense environments. Finding aggressive but dynamically feasible and collision-free trajectories in cluttered environments requires trajectory optimization and state estimation in the full state space of the vehicle, which is usually computationally infeasible on realistic timescales for real vehicles and sensors. We first build on previous work of van Nieuwstadt and Murray and Mellinger and Kumar, to show how a search process can be coupled with optimization in the output space of a differentially flat vehicle model to find aggressive trajectories that utilize the full maneuvering capabilities of a quadrotor. We further extend this work to vehicles with complex, Dubins-type dynamics and present a novel trajectory representation called a Dubins-Polynomial trajectory, which allows us to optimize trajectories for fixed-wing vehicles. To provide accurate state estimation for aggressive flight, we show how the Gaussian particle filter can be extended to allow laser rangefinder localization to be combined with a Kalman filter. This formulation allows similar estimation accuracy to particle filtering in the full vehicle state but with an order of magnitude more efficiency. We conclude with experiments demonstrating the execution of quadrotor and fixed-wing trajectories in cluttered environments. We show results of aggressive flight at speeds of up to 8m/s for the quadrotor and 11m/s for the fixed-wing aircraft.

关键词： Non-holonomic motion planning mobile and distributed robotics SLAM localization sensor fusion sensing and perception computer vision aerial robotics field and service robotics motion control mechanics design and control

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Estimation, Control, and Planning for Aggressive Flight With a Small Quadrotor With a Single Camera and IMU

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IEEE robotics AND AUTOMATION LETTERS 2017年第2期2卷 404-411页

作者： Loianno, Giuseppe Brunner, Chris McGrath, Gary Kumar, Vijay Univ Penn Gen Robot Automat Sensing & Percept Lab Phialdelphia PA 19103 USA Qualcomm Technol Inc San Diego CA 92121 USA

We address the state estimation, control, and planning for aggressive flight with a 150 cm diameter, 250 g quadrotor equipped only with a single camera and an inertial measurement unit (IMU). The use of smartphone grade hardware and the small scale provides an inexpensive and practical solution for autonomous flight in indoor environments. The key contributions of this paper are: 1) robust state estimation and control using only amonocular camera and an IMUat speeds of 4.5 m/s, accelerations of over 1.5 g, roll and pitch angles of up to 90., and angular rate of up to 800 degrees/s without requiring any structure in the environment;2) planning of dynamically feasible three-dimensional trajectories for slalom paths and flights through narrow windows;and 3) extensive experimental results showing aggressive flights through and around obstacles with large rotation angular excursions and accelerations.

关键词： aerial robotics optimization and optimal control sensor-based control

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Motion primitives and 3D path planning for fast flight through a forest

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INTERNATIONAL JOURNAL OF robotics RESEARCH 2015年第3期34卷 357-377页

作者： Paranjape, Aditya A. Meier, Kevin C. Shi, Xichen Chung, Soon-Jo Hutchinson, Seth McGill Univ Dept Mech Engn Montreal PQ H3A 2T5 Canada Univ Illinois Dept Elect & Comp Engn Urbana IL 61801 USA Univ Illinois Dept Aerosp Engn Urbana IL 61801 USA

This paper presents two families of motion primitives for enabling fast, agile flight through a dense obstacle field. The first family of primitives consists of a time-delay dependent 3D circular path between two points in space and the control inputs required to fly the path. In particular, the control inputs are calculated using algebraic equations which depend on the flight parameters and the location of the waypoint. Moreover, the transition between successive maneuver states, where each state is defined by a unique combination of constant control inputs, is modeled rigorously as an instantaneous switch between the two maneuver states following a time delay which is directly related to the agility of the robotic aircraft. The second family consists of aggressive turn-around (ATA) maneuvers which the robot uses to retreat from impenetrable pockets of obstacles. The ATA maneuver consists of an orchestrated sequence of three sets of constant control inputs. The duration of the first segment is used to optimize the ATA for the spatial constraints imposed by the turning volume. The motion primitives are validated experimentally and implemented in a simulated receding horizon control (RHC)-based motion planner. The paper concludes with inverse-design pointers derived from the primitives.

关键词： aerial robotics online path planning flight control motion primitives optimal control bio-inspired flight

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Rectilinear workspace partitioning for parallel coverage using multiple unmanned aerial vehicles

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ADVANCED robotics 2007年第1-2期21卷 105-120页

作者： Agarwal, Amit Hiot, Lim Meng Joo, Er Meng Nghia, Nguyen Trung Nanyang Technol Univ Intelligent Syst Ctr Singapore 637553 Singapore

Given a planar workpiece R, the objective of region coverage is to find an ordered list of waypoints and the geometry of paths between consecutive waypoints along which the centroid of a sensor footprint can be moved to efficiently trace a minimal superset of R. We consider the problem of maximally parallelizing the coverage of a contiguous rectilinear region represented by p is an element of R by dividing p amongst eta unmanned aerial vehicles (UAVs). The rates at which the UAVs can perform region coverage may differ. The optimum solution to this problem comprises a decomposition of P into eta parts such that the cost C-i of covering a part using UAV(i) is proportional to the relative rate at which the UAV can coverage. This problem, however, is NP-hard and we instead give a polynomial time algorithm for solving a closely related problem: divide p into eta parts that are each rectilinear, contiguous and whose areas are in the ratio of relative capabilities of the UAVs. Following the division of p, each part is covered by the corresponding UAV. We prove that our algorithm runs in O(N log N + eta N) time. To the best of our knowledge, this is the first time that an algorithm for solving our constrained partitioning problem has been reported.

关键词： polygon partitioning urban and airbase reconnaissance aerial robotics

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