Using a Mini-UAV to Support Wilderness Search and Rescue: Practices for Human-Robot Teaming

Goodrich, Michael A.; Cooper, Joseph L.; Adams, Julie A.; Humphrey, Curtis M.; Zeeman, R.; Buss, B.G.

doi:10.1109/ssrr.2007.4381284

Cited by 61 publications

(34 citation statements)

References 10 publications

(12 reference statements)

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“…The recent development of MAV technologies has provide such vehicles with capabilities to accomplish a variety of tasks such as search and rescue, disaster relief, surveillance of hostile territory, as well as inspection of hazardous environments such as indoor fire monitoring, investigation of hazardous or hostile buildings, disaster inspection of enclosed infrastructures (collapsed buildings, underground mines and subway stations after earthquakes or terrorist attacks, etc.) [1][2][3][4]. MAVs with autonomous capabilities are ideal candidates for these tasks since such environments are highly risky for human beings and inaccessible by ground robots.…”

Section: Introductionmentioning

confidence: 99%

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

Tang³

et al. 2015

Micromachines

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This paper presents a non-linear state observer-based integrated navigation scheme for estimating the attitude, position and velocity of micro aerial vehicles (MAV) operating in GPS-denied indoor environments, using the measurements from low-cost MEMS (micro electro-mechanical systems) inertial sensors and an RGB-D camera. A robust RGB-D visual odometry (VO) approach was developed to estimate the MAV's relative motion by extracting and matching features captured by the RGB-D camera from the environment. The state observer of the RGB-D visual-aided inertial navigation was then designed based on the invariant observer theory for systems possessing symmetries. The motion estimates from the RGB-D VO were fused with inertial and magnetic measurements from the onboard MEMS sensors via the state observer, providing the MAV with accurate estimates of its full six degree-of-freedom states. Implementations on a quadrotor MAV and indoor flight test results demonstrate that the resulting state observer is effective in estimating the MAV's states without relying on external navigation aids such as GPS. The properties of computational efficiency and simplicity in gain tuning make the proposed invariant observer-based navigation scheme appealing for actual MAV applications in indoor environments. OPEN ACCESSMicromachines 2015, 6 488

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Section: Introductionmentioning

confidence: 99%

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

Tang³

et al. 2015

Micromachines

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“…For this purpose, UAVs equipped with thermal or other sensors can be programmed to fly predefined search patterns at low altitudes -30 m to 150 m-, transmitting realtime imagery back to a ground station via a data link. Although less spread in Europe than in North America or Australia, it can be stated that the use of UAS for the so-called "wilderness SAR" is rapidly evolving (Goodrich et al, 2007). As the project targeted at search missions -not rescue missions-, the proposed system was designed to be integrated in the SAR context just as one more piece of the search workflow.…”

Section: Introductionmentioning

confidence: 99%

Searching Lost People With Uavs: The System and Results of the Close-Search Project

Molina

Colomina

Vitoria

et al. 2012

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:This paper will introduce the goals, concept and results of the project named CLOSE-SEARCH, which stands for 'Accurate and safe EGNOS-SoL Navigation for UAV-based low-cost Search-And-Rescue (SAR) operations'. The main goal is to integrate a medium-size, helicopter-type Unmanned Aerial Vehicle (UAV), a thermal imaging sensor and an EGNOS-based multi-sensor navigation system, including an Autonomous Integrity Monitoring (AIM) capability, to support search operations in difficult-to-access areas and/or night operations. The focus of the paper is three-fold. Firstly, the operational and technical challenges of the proposed approach are discussed, such as ultra-safe multi-sensor navigation system, the use of combined thermal and optical vision (infrared plus visible) for person recognition and Beyond-Line-Of-Sight communications among others. Secondly, the implementation of the integrity concept for UAV platforms is discussed herein through the AIM approach. Based on the potential of the geodetic quality analysis and on the use of the European EGNOS system as a navigation performance starting point, AIM approaches integrity from the precision standpoint; that is, the derivation of Horizontal and Vertical Protection Levels (HPLs, VPLs) from a realistic precision estimation of the position parameters is performed and compared to predefined Alert Limits (ALs). Finally, some results from the project test campaigns are described to report on particular project achievements. Together with actual Search-and-Rescue teams, the system was operated in realistic, user-chosen test scenarios. In this context, and specially focusing on the EGNOS-based UAV navigation, the AIM capability and also the RGB/thermal imaging subsystem, a summary of the results is presented.

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“…Key to the search task is the collection and comprehension of evidence [1]. The benefits of Unmanned Aerial Vehicles (UAVs) in evidence collection are well-established: they can rapidly acquire aerial imagery even in dangerous environments.…”

Section: Introductionmentioning

confidence: 99%

“…Most systems are equipped with cameras and are controlled by a UAV operator (who flies the UAV) and a sensor operator (who controls the camera and interprets the data) [1]. When multiple UAVs are used, the complexity of coordination means that they are normally flown in a fixed formation relative to one another at a fixed altitude above the ground.…”

Section: Introductionmentioning

confidence: 99%

Coordinated Search with a Swarm of UAVs

Waharte

Trigoni

Julier

2009

2009 6th IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops

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Abstract-Search is a fundamental task for Wilderness Search and Rescue that can greatly benefit from the use of a swarm of autonomous UAVs to survey the environment. The benefits are maximised if the UAVs coordinate their search activities with one another. In this poster, we present our preliminary work on developing coordination strategies for multiple UAVs. It is based on a distributed, grid-based probabilistic environmental model. We discuss the practicalities of the search task, present a simplified mathematical model of the environment and sensors, and present some preliminary simulation-based results. These clearly illustrate, even in a highly simplified case, the great benefits of coordinated search.

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Using a Mini-UAV to Support Wilderness Search and Rescue: Practices for Human-Robot Teaming

Cited by 61 publications

References 10 publications

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

Invariant Observer-Based State Estimation for Micro-Aerial Vehicles in GPS-Denied Indoor Environments Using an RGB-D Camera and MEMS Inertial Sensors

Searching Lost People With Uavs: The System and Results of the Close-Search Project

Coordinated Search with a Swarm of UAVs

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