Vision-based multi-UAV position estimation

Merino, Luís; Wiklund, Johan; Caballero, Fernando; Moe, Anders; Dios, J.R. Martínez-de; Forssén, Per-Erik; Nordberg, Klas; Ollero, A.

doi:10.1109/mra.2006.1678139

Cited by 62 publications

(36 citation statements)

References 22 publications

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“…However, recently, both WSNs and VSNs have begun to be studied together [3], [4]. Several survey papers deal with the overall architecture, characteristics and research directions of WVSNs with respect to topology control, event-driven operation, image processing, communication and networking and energy management [5]- [10].…”

Section: A Related Workmentioning

confidence: 99%

A Pervasive Network Control Algorithm for Multicamera Networks

Lee

Kim

et al. 2014

IEEE Sensors J.

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Abstract-Owing to the increasingly large volume and complexity of captured videos, renewable energy systems based on solar energy are of particular interest in the design of energy harvesting (EH) wireless visual sensor networks (WVSNs). Since additional energy consumption following image capture occurs owing to image processing, mote operation, data transmission, and reception, the capture rate significantly affects the lifetime of a node. To this end, we explore a novel energy-efficient framework for EH-WVSN design by developing an optimal algorithm named capture rate and pervasive network control for multicamera networks where the quality of service is maximized by obtaining optimal values for the capture rate, allocated energy, and transmit power, based on field of view-based networking in the presence of event and power acquisition patterns. Through simulations, we demonstrate the feasibility of EH-WVSNs in terms of energy consumption, energy allocation, and capture rate in a realistic scenario (parking surveillance).Index Terms-Capture rate, energy harvesting, visual sensor network, IEEE 802.15.4, field of view.

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Section: A Related Workmentioning

confidence: 99%

A Pervasive Network Control Algorithm for Multicamera Networks

Lee

Kim

et al. 2014

IEEE Sensors J.

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“…The main drawback of this method is the continuous accumulation of displacement errors for which no measure of uncertainty is provided. For a group of UAVs [12], a homography-based method is presented in which the observations of the common scene enables the robots to estimate their relative poses and localize with respect to a common frame of reference. Unfortunately, the planar scene assumption is unsuitable for many real-world scenarios (e.g., when flying near the ground or indoors).…”

Section: B Visual Odometry and Vision-aided Inertial Navigationmentioning

confidence: 99%

Cooperative vision-aided inertial navigation using overlapping views

Melnyk

Hesch

Roumeliotis

2012

2012 IEEE International Conference on Robotics and Automation

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Abstract-In this paper, we study the problem of Cooperative Localization (CL) for two robots, each equipped with an Inertial Measurement Unit (IMU) and a camera. We present an algorithm that enables the robots to exploit common features, observed over a sliding-window time horizon, in order to improve the localization accuracy of both vehicles. In contrast to existing CL methods, which require robot-to-robot distance and/or bearing measurements to resolve the robots' relative position and orientation (pose), our approach recovers the relative pose through indirect information from the commonly observed features. Moreover, we analyze the system observability properties to determine how many degrees of freedom (d.o.f.) of the relative transformation can be computed under different measurement scenarios. Lastly, we present simulation results to evaluate the performance of the proposed method.

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“…This builds a local map of the environment and transmits it to other robots in order to combine them and generate a more complete and accurate model for the whole team [3,17].…”

Section: Ralmentioning

confidence: 99%

“…(v) HERO2 detected the fire [20] and geolocalized it [3,17] computing the GPS coordinates of the fire. Then, HERO2 generated a new task (Extinguish(E1)) and inserted it in the multi-robot negotiation process.…”

Section: Description Of the Demonstration In The 'Alamillo' Parkmentioning

confidence: 99%

Distributed Service-Based Cooperation in Aerial/Ground Robot Teams Applied to Fire Detection and Extinguishing Missions

2010

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This paper presents a system for the coordination of aerial and ground robots for applications such as surveillance and intervention in emergency management. The overall system architecture is described. An important part for the coordination between robots is the task allocation strategy. A distributed market-based algorithm, called S + T, has been developed to solve the multi-robot task allocation problem in applications that require cooperation among the robots to accomplish all the tasks. Using this algorithm, robots can provide transport and communication relay services dynamically to other robots during the missions. Moreover, the paper presents a demonstration with a team of heterogeneous robots (aerial and ground) cooperating in a mission of fire detection and extinguishing.

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Vision-based multi-UAV position estimation

Cited by 62 publications

References 22 publications

A Pervasive Network Control Algorithm for Multicamera Networks

A Pervasive Network Control Algorithm for Multicamera Networks

Cooperative vision-aided inertial navigation using overlapping views

Distributed Service-Based Cooperation in Aerial/Ground Robot Teams Applied to Fire Detection and Extinguishing Missions

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