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RCAMP: A Resilient Communication-Aware Motion Planner for Mobile Robots with Autonomous Repair of Wireless Connectivity
KTH, Skolan för datavetenskap och kommunikation (CSC), Centra, Centrum för Autonoma System, CAS. KTH, Skolan för datavetenskap och kommunikation (CSC), Datorseende och robotik, CVAP.ORCID-id: 0000-0002-6716-1111
Purdue Univ, W Lafayette, IN 47907 USA..
Sapienza Univ Rome, DIAG, ALCOR Lab, Rome, Italy..
Sapienza Univ Rome, DIAG, ALCOR Lab, Rome, Italy..
Visa övriga samt affilieringar
2017 (Engelska)Ingår i: 2017 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS) / [ed] Bicchi, A Okamura, A, IEEE , 2017, s. 2010-2017Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

Mobile robots, be it autonomous or teleoperated, require stable communication with the base station to exchange valuable information. Given the stochastic elements in radio signal propagation, such as shadowing and fading, and the possibilities of unpredictable events or hardware failures, communication loss often presents a significant mission risk, both in terms of probability and impact, especially in Urban Search and Rescue (USAR) operations. Depending on the circumstances, disconnected robots are either abandoned, or attempt to autonomously back-trace their way to the base station. Although recent results in Communication-Aware Motion Planning can be used to effectively manage connectivity with robots, there are no results focusing on autonomously re-establishing the wireless connectivity of a mobile robot without back-tracing or using detailed a priori information of the network. In this paper, we present a robust and online radio signal mapping method using Gaussian Random Fields, and propose a Resilient Communication-Aware Motion Planner (RCAMP) that integrates the above signal mapping framework with a motion planner. RCAMP considers both the environment and the physical constraints of the robot, based on the available sensory information. We also propose a self-repair strategy using RCMAP, that takes both connectivity and the goal position into account when driving to a connection-safe position in the event of a communication loss. We demonstrate the proposed planner in a set of realistic simulations of an exploration task in single or multi-channel communication scenarios.

Ort, förlag, år, upplaga, sidor
IEEE , 2017. s. 2010-2017
Serie
IEEE International Conference on Intelligent Robots and Systems, ISSN 2153-0858
Nyckelord [en]
Mobile Robots, Self-Repair, Wireless Communication, Communication-Aware Motion Planning
Nationell ämneskategori
Elektroteknik och elektronik
Identifikatorer
URN: urn:nbn:se:kth:diva-225803DOI: 10.1109/IROS.2017.8206020ISI: 000426978202045Scopus ID: 2-s2.0-85041962473ISBN: 978-1-5386-2682-5 (tryckt)OAI: oai:DiVA.org:kth-225803DiVA, id: diva2:1196086
Konferens
IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), SEP 24-28, 2017, Vancouver, CANADA
Anmärkning

QC 20180409

Tillgänglig från: 2018-04-09 Skapad: 2018-04-09 Senast uppdaterad: 2019-04-09Bibliografiskt granskad
Ingår i avhandling
1. Enhancing geometric maps through environmental interactions
Öppna denna publikation i ny flik eller fönster >>Enhancing geometric maps through environmental interactions
2018 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

The deployment of rescue robots in real operations is becoming increasingly commonthanks to recent advances in AI technologies and high performance hardware. Rescue robots can now operate for extended period of time, cover wider areas andprocess larger amounts of sensory information making them considerably more usefulduring real life threatening situations, including both natural or man-made disasters.

In this thesis we present results of our research which focuses on investigating ways of enhancing visual perception for Unmanned Ground Vehicles (UGVs) through environmental interactions using different sensory systems, such as tactile sensors and wireless receivers.

We argue that a geometric representation of the robot surroundings built upon vision data only, may not suffice in overcoming challenging scenarios, and show that robot interactions with the environment can provide a rich layer of new information that needs to be suitably represented and merged into the cognitive world model. Visual perception for mobile ground vehicles is one of the fundamental problems in rescue robotics. Phenomena such as rain, fog, darkness, dust, smoke and fire heavily influence the performance of visual sensors, and often result in highly noisy data, leading to unreliable or incomplete maps.

We address this problem through a collection of studies and structure the thesis as follow:Firstly, we give an overview of the Search & Rescue (SAR) robotics field, and discuss scenarios, hardware and related scientific questions.Secondly, we focus on the problems of control and communication. Mobile robotsrequire stable communication with the base station to exchange valuable information. Communication loss often presents a significant mission risk and disconnected robotsare either abandoned, or autonomously try to back-trace their way to the base station. We show how non-visual environmental properties (e.g. the WiFi signal distribution) can be efficiently modeled using probabilistic active perception frameworks based on Gaussian Processes, and merged into geometric maps so to facilitate the SAR mission. We then show how to use tactile perception to enhance mapping. Implicit environmental properties such as the terrain deformability, are analyzed through strategic glancesand touches and then mapped into probabilistic models.Lastly, we address the problem of reconstructing objects in the environment. Wepresent a technique for simultaneous 3D reconstruction of static regions and rigidly moving objects in a scene that enables on-the-fly model generation. Although this thesis focuses mostly on rescue UGVs, the concepts presented canbe applied to other mobile platforms that operates under similar circumstances. To make sure that the suggested methods work, we have put efforts into design of user interfaces and the evaluation of those in user studies.

Ort, förlag, år, upplaga, sidor
Stockholm: KTH Royal Institute of Technology, 2018. s. 58
Serie
TRITA-EECS-AVL ; 2018:26
Nyckelord
Gaussian Processes Robotics UGV Active perception geometric maps
Nationell ämneskategori
Teknik och teknologier
Forskningsämne
Datalogi
Identifikatorer
urn:nbn:se:kth:diva-225957 (URN)978-91-7729-720-8 (ISBN)
Disputation
2018-04-18, F3, Lindstedtsvägen 26, Sing-Sing, floor 2, KTH Campus, Stockholm, 10:00 (Engelska)
Opponent
Handledare
Forskningsfinansiär
EU, FP7, Sjunde ramprogrammet
Anmärkning

QC 20180411

Tillgänglig från: 2018-04-11 Skapad: 2018-04-11 Senast uppdaterad: 2018-04-11Bibliografiskt granskad

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Av författaren/redaktören
Caccamo, SergioÖgren, Petter
Av organisationen
Centrum för Autonoma System, CASDatorseende och robotik, CVAP
Elektroteknik och elektronik

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