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1.
Icebergs pose many challenges to offshore operations in the Arctic Ocean and sub‐arctic regions. They could damage underwater infrastructure such as pipelines, and disrupt marine transportation. The below‐water shape of an iceberg is a key factor for iceberg management in the North Atlantic Ocean because it affects the iceberg towing plans and iceberg drift patterns. In recent years, unmanned platforms have been proposed as potential candidates for underwater iceberg mapping. Compared to a conventional ship‐based iceberg survey, using unmanned platforms is more efficient and safer. In this paper, we present research using a hybrid underwater glider to measure the underwater shape of an iceberg. The vehicle is equipped with a mechanical scanning sonar for range sensing and iceberg mapping, and a guidance system is designed to use the sonar measurements for guiding the vehicle to circumnavigate an iceberg at the desired standoff distance. Several field experiments have been conducted on an iceberg to evaluate the system performance. With repeated observations, the underside of the target iceberg was successfully reconstructed, and iceberg shape comparisons are presented. 相似文献
2.
This paper presents a teach‐and‐repeat path‐following method for an autonomous underwater vehicle (AUV) navigating long distances in environments where external navigation aides are denied. This method utilizes sonar images to construct a series of reference views along a path, stored as a topological map. The AUV can then renavigate along this path, either to return to the start location or to repeat the route. Utilizing unique assumptions about the sonar image‐generation process, this system exhibits robust image‐matching capabilities, providing observations to a discrete Bayesian filter that maintains an estimate of progress along the path. Image‐matching also provides an estimate of offset from the path, allowing the AUV to correct its heading and effectively close the gap. Over a series of field trials, this system demonstrated online control of an AUV in the ocean environment of Holyrood Arm, Newfoundland and Labrador, Canada. The system was implemented on an International Submarine Engineering Ltd. Explorer AUV and performed multiple path completions over both a 1 and 5 km track. These trials illustrated an AUV operating in a fully autonomous mode, in which navigation was driven solely by sensor feedback and adaptive control. Path‐following performance was as desired, with the AUV maintaining close offset to the path. 相似文献
3.
Zuhayr Rymansaib Benjamin Thomas Alfred Anthony Treloar Benjamin Metcalfe Peter Wilson Alan Hunter 《野外机器人技术杂志》2023,40(5):983-1002
Underwater crime scene investigation and emergency response are tasks typically carried out by divers constituting part of a specialist team. Operating in such dynamic environments, often with poor visibility and risk of concealed hazards, can be time consuming and dangerous. Autonomous uncrewed vessels with underwater acoustic imaging sensors have been used for similar purposes in other fields (e.g., hydrography, naval mine countermeasures [MCMS], etc.) but have not been adopted in this specific application domain. The Police Robot for Inspection and Mapping of underwater Evidence (PRIME) is an autonomous uncrewed surface vessel that is being developed for this purpose. It is a novel application of existing robotic technology that is intended to be used within an end-to-end police and emergency underwater search process. It aims to enhance the effectiveness, efficiency, and safety of divers by autonomously locating and highlighting target objects or regions of interest, as well as benign regions, thereby reducing their time spent underwater. Side-scan imaging sonars are used to sense the underwater environment using techniques leveraged from the similar application domain of naval MCMs. The system autonomously generates actionable intelligence in the form of simplified coverage and anomaly maps for easy interpretation by the dive team. These are communicated to shore in real-time and georeferenced on satellite maps. This paper details the PRIME system prototype and presents results from initial field experimentation. The prototype has been operated in various urban, shallow-water environments. The experimental results shown here were collected in Bristol Harbour (the UK) with a water depth of approximately 5 m. In the experiment, a clothed mannequin resembling a human body was deployed on the muddy floor. Autonomous searches were executed and the body was detected successfully as an anomaly against the background, illustrating the feasibility and viability of the system as an autonomous robotic aid for locating missing persons in a representative, unstructured, and dynamic real-world environment. 相似文献
4.
Troy P. Cordie Tirthankar Bandyopadhyay Jonathan Roberts Matthew Dunbabin Kelly Greenop Ross Dungavell Ryan Steindl 《野外机器人技术杂志》2019,36(4):641-655
Robotic inspection often relies on building custom platforms for each new deployment; this is a luxury that urban search and rescue (USAR) robots do not have when time is of critical importance. A significant factor for robots deployed in disaster areas is the varying size of voids and access ways in their path. These situations require platforms that can quickly reconfigure on location. With these challenges in mind, we present the NeWheel system: An in‐field reconfigurable robotic platform that allows mobility changes before, and during, deployment. The NeWheel platform also has the advantage of being small enough to be person‐deployable and to travel as checked luggage on a commercial flight. This field report presents the results and learnings from three field trips on Peel Island located off the coast of Brisbane, Australia. These field trips featured the deployment of the NeWheel system in multiple configurations to inspect and map inside historic dilapidated buildings. It demonstrates the potential of the NeWheel in buildings cluttered with debris and with unstable flooring whether they are historically important or in USAR contexts. 相似文献
5.
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ek Vojt ch &#x;alanský Karel Zimmermann Tom&#x; Svoboda 《野外机器人技术杂志》2019,36(4):696-709
We consider the problem of active victim segmentation during a search‐and‐rescue (SAR) exploration mission. The robot is equipped with a multimodal sensor suite consisting of a camera, lidar, and pan‐tilt thermal sensor. The robot enters an unknown scene, builds a 3D model incrementally, and the proposed method simultaneously (a) segments the victims from incomplete multimodal measurements and (b) controls the motion of the thermal camera. Both of these tasks are difficult due to the lack of natural training data and the limited number of real‐world trials. In particular, we overcome the absence of training data for the segmentation task by employing a manually designed generative model, which provides a semisynthetic training data set. The limited number of real‐world trials is tackled by self‐supervised initialization and optimization‐based guiding of the motion control learning. In addition to that, we provide a quantitative evaluation of the proposed method on several real testing scenarios using the real SAR robot. Finally, we also provide a data set which will allow for further development of algorithms on the real data. 相似文献
6.
Russell Buchanan Lorenz Wellhausen Marko Bjelonic Tirthankar Bandyopadhyay Navinda Kottege Marco Hutter 《野外机器人技术杂志》2021,38(1):68-84
Legged robots are exceedingly versatile and have the potential to navigate complex, confined spaces due to their many degrees of freedom. As a result of the computational complexity, there exist no online planners for perceptive whole‐body locomotion of robots in tight spaces. In this paper, we present a new method for perceptive planning for multilegged robots, which generates body poses, footholds, and swing trajectories for collision avoidance. Measurements from an onboard depth camera are used to create a three‐dimensional map of the terrain around the robot. We randomly sample body poses then smooth the resulting trajectory while satisfying several constraints, such as robot kinematics and collision avoidance. Footholds and swing trajectories are computed based on the terrain, and the robot body pose is optimized to ensure stable locomotion while not colliding with the environment. Our method is designed to run online on a real robot and generate trajectories several meters long. We first tested our algorithm in several simulations with varied confined spaces using the quadrupedal robot ANYmal. We also simulated experiments with the hexapod robot Weaver to demonstrate applicability to different legged robot configurations. Then, we demonstrated our whole‐body planner in several online experiments both indoors and in realistic scenarios at an emergency rescue training facility. ANYmal, which has a nominal standing height of 80 cm and a width of 59 cm, navigated through several representative disaster areas with openings as small as 60 cm. Three‐meter trajectories were replanned with 500 ms update times. 相似文献
7.
Autonomous navigation of microaerial vehicles in environments that are simultaneously GPS‐denied and visually degraded, and especially in the dark, texture‐less and dust‐ or smoke‐filled settings, is rendered particularly hard. However, a potential solution arises if such aerial robots are equipped with long wave infrared thermal vision systems that are unaffected by darkness and can penetrate many types of obscurants. In response to this fact, this study proposes a keyframe‐based thermal–inertial odometry estimation framework tailored to the exact data and concepts of operation of thermal cameras. The front‐end component of the proposed solution utilizes full radiometric data to establish reliable correspondences between thermal images, as opposed to operating on rescaled data as previous efforts have presented. In parallel, taking advantage of a keyframe‐based optimization back‐end the proposed method is suitable for handling periods of data interruption which are commonly present in thermal cameras, while it also ensures the joint optimization of reprojection errors of 3D landmarks and inertial measurement errors. The developed framework was verified with respect to its resilience, performance, and ability to enable autonomous navigation in an extensive set of experimental studies including multiple field deployments in severely degraded, dark, and obscurants‐filled underground mines. 相似文献
8.
It is essential to provide disaster relief assistance after coal mine explosions. Often, it is life‐threatening for rescuers to enter an accident scene blindly; therefore, a coal mine rescue robot (CMRR) has been developed. However, the application of the CMRR has not proven satisfactory after decades of development. To solve this problem, we summarize the reasons for this disappointing state and address the technical challenges of the CMRR. Based on these reasons and the associated technical challenges, two generations of tracked robots have been developed. The China University of Mining Technology‐V (CUMT‐V) (A) robot was first developed and its walking system, body support system, communication system, environmental awareness system, and control system are described in detail. A performance test was performed on the CUMT‐V (A) robot and some problems were encountered. To address these problems, we designed the CUMT‐V (B) robot. The field test was conducted in Shanxi province, China, in August 2016. The application results show that the robot has good adaptability to complex terrain and high reliability in terms of environmental awareness and data transmission. In conclusion, the robot is nearing practical applications. 相似文献
9.
John Peterson Weilin Li Brian Cesar‐Tondreau John Bird Kevin Kochersberger Wojciech Czaja Morgan McLean 《野外机器人技术杂志》2019,36(4):818-845
This paper discusses the results of a field experiment conducted at Savannah River National Laboratory to test the performance of several algorithms for the localization of radioactive materials. In this multirobot system, both an unmanned aerial vehicle, a custom hexacopter, and an unmanned ground vehicle (UGV), the ClearPath Jackal, equipped with γ‐ray spectrometers, were used to collect data from two radioactive source configurations. Both the Fourier scattering transform and the Laplacian eigenmap algorithms for source detection were tested on the collected data sets. These algorithms transform raw spectral measurements into alternate spaces to allow clustering to detect trends within the data which indicate the presence of radioactive sources. This study also presents a point source model and accompanying information‐theoretic active exploration algorithm. Field testing validated the ability of this model to fuse aerial and ground collected radiation measurements, and the exploration algorithm’s ability to select informative actions to reduce model uncertainty, allowing the UGV to locate radioactive material online. 相似文献
10.
For micro aerial vehicles (MAVs) involved in search and rescue missions, the ability to locate the source of a distress sound signal is significantly important and allows fast localization of victims and rescuers during nighttime, through foliage and in dust, fog, and smoke. Most emergency sound sources, such as safety whistles and personal alarms, generate a narrowband signal that is difficult to localize by human listeners or with the common localization methods suitable for broadband sounds. In this paper, we present three methods for MAV‐based emergency sound localization system. The first method involves designing a new emergency source for immediate localization by the MAV using a common localization method. The other two novel methods allow localizing the currently available emergency sources, or other narrowband sounds in general, that are difficult to localize due to the periodicity in the sequence of sound samples. The second method exploits the Doppler shift in the sound frequency, caused due to the motion of the MAV and the dynamics of the MAV to assist with the localization. The third method involves active control of the robot's attitude and fusing acoustic and attitude measurements for achieving accurate and robust estimates. We evaluate our methods in real‐world experiments with real flying robots. 相似文献
11.
This paper presents a real‐time and channel‐invariant visibility enhancement algorithm using a hybrid image enhancement approach. The proposed method is initially motivated by an underwater visual simultaneous localization and mapping (SLAM) failure in a turbid medium. The environments studied contain various particles and are dominated by a different image degradation model. Targeting image enhancement for degraded images but not being limited to it, the proposed method provides a highly effective solution for both color and gray images with substantial improvement in the process time compared to conventional methods. The proposed method introduces a hybrid scheme of two image enhancement modules: a model‐based (extensive) enhancement and a model‐free (immediate) enhancement. The proposed method is validated by using simulated synthetic color images and real‐world color and grayscale underwater images. Real‐world validation is performed in various environments such as hazy indoor, smoky indoor, and underwater. Using the ground truth trajectory or clear images acquired from the same area but without turbidity, we evaluate the proposed visibility enhancement and camera registration improvement for a feature based (ORB‐SLAM2), a direct (LSD‐SLAM), and a visual underwater SLAM application. 相似文献
12.
Danilo Tardioli Luis Riazuelo Domenico Sicignano Carlos Rizzo Francisco Lera Jos L. Villarroel Luis Montano 《野外机器人技术杂志》2019,36(6):1074-1101
The work reported in this article describes the research advances and the lessons learned by the Robotics, Perception and Real‐Time group over a decade of research in the field of ground robotics in confined environments. This study has primarily focused on localization, navigation, and communications in tunnel‐like environments. As will be discussed, this type of environment presents several special characteristics that often make well‐established techniques fail. The aim is to share, in an open way, the experience, errors, and successes of this group with the robotics community so that those that work in such environments can avoid (some of) the errors made. At the very least, these findings can be readily taken into account when designing a solution, without needing to sift through the technical details found in the papers cited within this text. 相似文献
13.
The Mars Science Laboratory (MSL) Curiosity rover landed in Gale crater in August of 2012 on its mission to explore Mt. Sharp as the first planetary rover to collect and analyze rock and regolith samples. On this new mission, sampling operations were conceived to be executed serially and in situ, on a “sample chain” along which sample would be collected, then processed, then delivered to sample analysis instruments, analyzed there, and then discarded so the chain could be repeated. This paper describes the evolution of this relatively simple chain into a richer sampling network, responding to science and engineering desires that came into focus only as the mission matured, scientific discoveries were made, and anomalies were encountered. The rover flight and ground system architectures retained significant heritage from past missions, while extending capabilities in anticipation of the need for adaptation. As evolution occurred, the architecture permitted nimble extension of sampling behavior without time‐consuming flight software updates or significant impact to daily operations. This paper presents the major components of this architecture and discusses some of the results of successful adaptation across thousands of Sols of Mars operations. 相似文献
14.
15.
Tobias Klamt Max Schwarz Christian Lenz Lorenzo Baccelliere Domenico Buongiorno Torben Cichon Antonio DiGuardo David Droeschel Massimiliano Gabardi Malgorzata Kamedula Navvab Kashiri Arturo Laurenzi Daniele Leonardis Luca Muratore Dmytro Pavlichenko Arul S. Periyasamy Diego Rodriguez Massimiliano Solazzi Antonio Frisoli Michael Gustmann Jürgen Roßmann Uwe Süss Nikos G. Tsagarakis Sven Behnke 《野外机器人技术杂志》2020,37(5):889-919
Solving mobile manipulation tasks in inaccessible and dangerous environments is an important application of robots to support humans. Example domains are construction and maintenance of manned and unmanned stations on the moon and other planets. Suitable platforms require flexible and robust hardware, a locomotion approach that allows for navigating a wide variety of terrains, dexterous manipulation capabilities, and respective user interfaces. We present the CENTAURO system which has been designed for these requirements and consists of the Centauro robot and a set of advanced operator interfaces with complementary strength enabling the system to solve a wide range of realistic mobile manipulation tasks. The robot possesses a centaur‐like body plan and is driven by torque‐controlled compliant actuators. Four articulated legs ending in steerable wheels allow for omnidirectional driving as well as for making steps. An anthropomorphic upper body with two arms ending in five‐finger hands enables human‐like manipulation. The robot perceives its environment through a suite of multimodal sensors. The resulting platform complexity goes beyond the complexity of most known systems which puts the focus on a suitable operator interface. An operator can control the robot through a telepresence suit, which allows for flexibly solving a large variety of mobile manipulation tasks. Locomotion and manipulation functionalities on different levels of autonomy support the operation. The proposed user interfaces enable solving a wide variety of tasks without previous task‐specific training. The integrated system is evaluated in numerous teleoperated experiments that are described along with lessons learned. 相似文献
16.
Search and rescue operations are necessary in locating, assisting and recovering individuals lost or in distress. In Australia, land-based search and rescue roles require a range of physically demanding tasks undertaken in dynamic and challenging environments. The aim of the current research was to identify and characterise the physically demanding tasks inherent to search and rescue operation personnel within Australia. These aims were met through a subjective job task analysis approach. In total, 11 criterion tasks were identified by personnel. These tasks were the most physically demanding, frequently occurring and operationally important tasks to these specialist roles. Muscular strength was the dominant fitness component for 7 of the 11 tasks. In addition to the discrete criterion tasks, an operational scenario was established. With the tasks and operational scenario identified, objective task analysis procedures can be undertaken so that practitioners can implement evidence-based strategies, such as physical selection procedures and task-based physical training programs, commensurate with the physical demands of search and rescue job roles.
Practitioner Summary: The identification of physically demanding tasks amongst specialist emergency service roles predicates health and safety strategies which can be incorporated into organisations. Knowledge of physical task parameters allows employers to mitigate injury risk through the implementation of strategies modelled on the precise physical demands of the role. 相似文献
17.
Eimei Oyama Naoji Shiroma Norifumi Watanabe Arvin Agah Takashi Omori Natsuo Suzuki 《Advanced Robotics》2016,30(3):151-164
Performing general human behavior by experts’ navigation is expected to be realized as wearable technologies and computing systems are further developed. We have proposed and developed the prototype of the advanced behavior navigation system (BNS) using augmented reality technology. Utilizing the BNS, an expert can guide a non-expert to perform a variety of tasks. The BNSs are useful in tasks to be performed in harsh and hazardous environments, such as factories, construction sites, and areas affected by natural disasters (e.g. earthquakes and tsunamis). In this paper, we present a BNS that is specifically designed to operate in harsh environments, with characteristics such as wet or dusty conditions. The implementation, experimental results, and evaluation of the BNS prototypes are presented. 相似文献
18.
Christophe De Wagter Rick Ruijsink Ewoud J. J. Smeur Kevin G. van Hecke Freek van Tienen Erik van der Horst Bart D. W. Remes 《野外机器人技术杂志》2018,35(6):937-960
To participate in the Outback Medical Express UAV Challenge 2016, a vehicle was designed and tested that can autonomously hover precisely, takeoff and land vertically, fly fast forward efficiently, and use computer vision to locate a person and a suitable landing location. The vehicle is a novel hybrid tail‐sitter combining a delta‐shaped biplane fixed‐wing and a conventional helicopter rotor. The rotor and wing are mounted perpendicularly to each other,and the entire vehicle pitches down to transition from hover to fast forward flight where the rotor serves as propulsion. To deliver sufficient thrust in hover while still being efficient in fast forward flight, a custom rotor system was designed. The theoretical design was validated with energy measurements, wind tunnel tests, and application in real‐world missions. A rotor‐head and corresponding control algorithm were developed to allow transitioning flight with the nonconventional rotor dynamics that are caused by the fuselage rotor interaction. Dedicated electronics were designed that meet vehicle needs and comply with regulations to allow safe flight beyond visual line of sight. Vision‐based search and guidance algorithms running on a stereo‐vision fish‐eye camera were developed and tested to locate a person in cluttered terrain never seen before. Flight tests and a competition participation illustrate the applicability of the DelftaCopter concept. 相似文献
19.
In this study, we use unmanned aerial vehicles equipped with multispectral cameras to search for bodies in maritime rescue operations. A series of flights were performed in open‐water scenarios in the northwest of Spain, using a certified aquatic rescue dummy in dangerous areas and real people when the weather conditions allowed it. The multispectral images were aligned and used to train a convolutional neural network for body detection. An exhaustive evaluation was performed to assess the best combination of spectral channels for this task. Three approaches based on a MobileNet topology were evaluated, using (a) the full image, (b) a sliding window, and (c) a precise localization method. The first method classifies an input image as containing a body or not, the second uses a sliding window to yield a class for each subimage, and the third uses transposed convolutions returning a binary output in which the body pixels are marked. In all cases, the MobileNet architecture was modified by adding custom layers and preprocessing the input to align the multispectral camera channels. Evaluation shows that the proposed methods yield reliable results, obtaining the best classification performance when combining green, red‐edge, and near‐infrared channels. We conclude that the precise localization approach is the most suitable method, obtaining a similar accuracy as the sliding window but achieving a spatial localization close to 1 m. The presented system is about to be implemented for real maritime rescue operations carried out by Babcock Mission Critical Services Spain. 相似文献
20.
Gaining information about an unknown gas source is a task of great importance with applications in several areas, including responding to gas leaks or suspicious smells, quantifying sources of emissions, or in an emergency response to an industrial accident or act of terrorism. In this paper, a method to estimate the source term of a gaseous release using measurements of concentration obtained from an unmanned aerial vehicle (UAV) is described. The source term parameters estimated include the three‐dimensional location of the release, its emission rate and other important variables needed to forecast the spread of the gas using an atmospheric transport and dispersion model. The parameters of the source are estimated by fusing concentration observations from a gas detector on‐board the aircraft, with meteorological data and an appropriate model of dispersion. Two models are compared in this paper, both derived from analytical solutions to the advection–diffusion equation. Bayes’ theorem, implemented using a sequential Monte Carlo algorithm, is used to estimate the source parameters to take into account the large uncertainties in the observations and formulated models. The system is verified with novel, outdoor, fully automated experiments, where observations from the UAV are used to estimate the parameters of a diffusive source. The estimation performance of the algorithm is assessed subject to various flight path configurations and wind speeds. Observations and lessons learned during these unique experiments are discussed, and areas for future research are identified. 相似文献
