From ERL to MBZIRC: Development of An Aerial-Ground Robotic Team for Search and Rescue

This chapter describes the efforts of the LARICS team in the 2019 European Robotics League (ERL) Emergency Robots and the 2020 Mohamed Bin Zayed International Robotics Challenge (MBZIRC) robotics competitions. We focus on the implementation of hardware and software modules that enable the deployment of aerial-ground robotic teams in unstructured environments for joint missions. In addition to the overall system specification, we outline the main algorithms for operation in such conditions: autonomous exploration of unknown environments and detection of objects of interest. Analysis of the results shows the success of the developed system in the competition arena of two of the largest outdoor robotics challenges. Throughout the chapter, we highlight the evolution of the robotic system based on the experience gained in the ERL competition. We conclude the chapter with key findings and additional improvement ideas to advance the state of the art in search and rescue applications of heterogeneous robotic teams.

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Utilización de la Comunicación por Radiofrecuencia para la Detección de Vehículos en Movimiento: Revisión del Estado del Arte

KnE Engineering ◽

10.18502/keg.v3i1.1503 ◽

2018 ◽

Vol 3 (1) ◽

pp. 821 ◽

Cited By ~ 1

Author(s):

Antony García ◽

Yessica Sáez ◽

José Muñoz ◽

Ignacio Chang ◽

Héctor Montes Franceschi

Keyword(s):

Fixed Point ◽

Public Transportation ◽

State Of The Art ◽

Low Cost ◽

The State ◽

Visual Disability ◽

Visual Disabilities ◽

The Public ◽

Detection Of Objects ◽

Public Transportation System

This article presents the state of the art on the use of radiofrequency communication for the detection of objects and vehicles in motion, through the interaction between transmitter and receiver devices using ISM (Industrial, Scientific and Medical) bands. By quantifying parameters such as the absence or presence of signals and their intensity, it is possible to approximate the distance between an emitting device and a receiver, localized in the vehicle and a fixed point, respectively . The study of the methodologies used in this article aims to develop a system oriented to guide people with visual disabilities in the public transportation system, taking advantage of the main characteristics of radiofrequency communication: low cost, easy implementation and full compatibility with electronic boards built on embedded systems.Keywords: radiofrequency, ISM bands, detection of vehicles in motion, support for visual disability people, ETA

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Optimal Frontier-Based Autonomous Exploration in Unconstructed Environment Using RGB-D Sensor

Sensors ◽

10.3390/s20226507 ◽

2020 ◽

Vol 20 (22) ◽

pp. 6507 ◽

Cited By ~ 1

Author(s):

Liang Lu ◽

Carlos Redondo ◽

Pascual Campoy

Keyword(s):

Clustering Algorithm ◽

Information Gain ◽

State Of The Art ◽

Search And Rescue ◽

Autonomous Exploration ◽

Aerial Robots ◽

Exploration Time ◽

Feasible Path ◽

Path Planner ◽

To Receive

Aerial robots are widely used in search and rescue applications because of their small size and high maneuvering. However, designing an autonomous exploration algorithm is still a challenging and open task, because of the limited payload and computing resources on board UAVs. This paper presents an autonomous exploration algorithm for the aerial robots that shows several improvements for being used in the search and rescue tasks. First of all, an RGB-D sensor is used to receive information from the environment and the OctoMap divides the environment into obstacles, free and unknown spaces. Then, a clustering algorithm is used to filter the frontiers extracted from the OctoMap, and an information gain based cost function is applied to choose the optimal frontier. At last, the feasible path is given by A* path planner and a safe corridor generation algorithm. The proposed algorithm has been tested and compared with baseline algorithms in three different environments with the map resolutions of 0.2 m, and 0.3 m. The experimental results show that the proposed algorithm has a shorter exploration path and can save more exploration time when compared with the state of the art. The algorithm has also been validated in the real flight experiments.

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The advances in the state of the art of modeling and simulation: Discrete event system specification (DEVS)

SIMULATION ◽

10.1177/0037549718758429 ◽

2018 ◽

Vol 94 (4) ◽

pp. 279-280

Author(s):

Navonil Mustafee ◽

Saurabh Mittal ◽

Saikou Diallo ◽

Gregory Zacharewicz

Keyword(s):

Modeling And Simulation ◽

State Of The Art ◽

Discrete Event ◽

Discrete Event System ◽

The State ◽

System Specification ◽

Discrete Event System Specification ◽

Event System

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Temporal and non-temporal contextual saliency analysis for generalized wide-area search within unmanned aerial vehicle (UAV) video

The Visual Computer ◽

10.1007/s00371-021-02264-6 ◽

2021 ◽

Author(s):

Simon G. E. Gökstorp ◽

Toby P. Breckon

Keyword(s):

Short Term Memory ◽

State Of The Art ◽

Saliency Detection ◽

Visual Saliency ◽

Temporal Reasoning ◽

The State ◽

Search And Rescue ◽

Wide Area ◽

Deep Model ◽

The Impact

AbstractUnmanned aerial vehicles (UAV) can be used to great effect for wide-area searches such as search and rescue operations. UAV enable search and rescue teams to cover large areas more efficiently and in less time. However, using UAV for this purpose involves the creation of large amounts of data, typically in video format, which must be analysed before any potential findings can be uncovered and actions taken. This is a slow and expensive process which can result in significant delays to the response time after a target is seen by the UAV. To solve this problem we propose a deep model architecture using a visual saliency approach to automatically analyse and detect anomalies in UAV video. Our Temporal Contextual Saliency (TeCS) approach is based on the state-of-the-art in visual saliency detection using deep Convolutional Neural Networks (CNN) and considers local and scene context, with novel additions in utilizing temporal information through a convolutional Long Short-Term Memory (LSTM) layer and modifications to the base model architecture. We additionally evaluate the impact of temporal vs non-temporal reasoning for this task. Our model achieves improved results on a benchmark dataset with the addition of temporal reasoning showing significantly improved results compared to the state-of-the-art in saliency detection.

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Practical Picture Processing

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100051700 ◽

1974 ◽

Vol 32 ◽

pp. 338-339

Author(s):

T. A. Welton

Keyword(s):

Radiation Damage ◽

Coherence Length ◽

Spatial Information ◽

State Of The Art ◽

Coherent Radiation ◽

The State ◽

Energy Spread ◽

Electron Micrograph ◽

Picture Processing ◽

Molecular Skeleton

Various authors have emphasized the spatial information resident in an electron micrograph taken with adequately coherent radiation. In view of the completion of at least one such instrument, this opportunity is taken to summarize the state of the art of processing such micrographs. We use the usual symbols for the aberration coefficients, and supplement these with £ and 6 for the transverse coherence length and the fractional energy spread respectively. He also assume a weak, biologically interesting sample, with principal interest lying in the molecular skeleton remaining after obvious hydrogen loss and other radiation damage has occurred.

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