WatchBot: A building maintenance and surveillance system based on autonomous robots

López, Joaquín; Pérez, Diego Gutiérrez; Paz, Enrique; Santana, Alejandro Escudero

doi:10.1016/j.robot.2013.06.012

Cited by 49 publications

(17 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this case, the robot can improve the services provided in the hospital through autonomous navigation based on following a path. More recently, in [39] a team of robots that cooperate in a building developing maintenance and surveillance tasks was presented.…”

Section: Real World Applicationsmentioning

confidence: 99%

Learning fuzzy controllers in mobile robotics with embedded preprocessing

Rodríguez-Fdez¹,

Mucientes²,

Bugarín³

2015

Applied Soft Computing

View full text Add to dashboard Cite

The automatic design of controllers for mobile robots usually requires two stages. In the first stage, sensorial data are preprocessed or transformed into high level and meaningful values of variables which are usually defined from expert knowledge. In the second stage, a machine learning technique is applied to obtain a controller that maps these high level variables to the control commands that are actually sent to the robot. This paper describes an algorithm that is able to embed the preprocessing stage into the learning stage in order to get controllers directly starting from sensorial raw data with no expert knowledge involved. Due to the high dimensionality of the sensorial data, this approach uses Quantified Fuzzy Rules (QFRs), that are able to transform low-level input variables into high-level input variables, reducing the dimensionality through summarization. The proposed learning algorithm, called Iterative Quantified Fuzzy Rule Learning (IQFRL), is based on genetic programming. IQFRL is able to learn rules with different structures, and can manage linguistic variables with multiple granularities. The algorithm has been tested with the implementation of the wall-following behavior both in several realistic simulated environments with different complexity and on a Pioneer 3-AT robot in two real environments. Results have been compared with several well-known learning algorithms combined with different data preprocessing techniques, showing that IQFRL exhibits a better and statistically significant performance. Moreover, three real world applications for which IQFRL plays a central role are also presented: path and object tracking with static and moving obstacles avoidance.

show abstract

Section: Real World Applicationsmentioning

confidence: 99%

Learning fuzzy controllers in mobile robotics with embedded preprocessing

Rodríguez-Fdez¹,

Mucientes²,

Bugarín³

2015

Applied Soft Computing

View full text Add to dashboard Cite

show abstract

“…Methodologies to describe agent oriented systems engineering (AOSE) [5] have emerged in order to be able to work in a multi-agent environment, while in this work we used the HARMS model to communicate between all the agents including human interface [3]. A solution for surveillance and maintenance of autonomous robots was developed under the name of WatchBot, with can be used for surveillance and for other purposes [6]. Perhaps research on taking advantage of autonomous multi and heterogeneous robots has been extended recently, opening the door to new applications for fire fighters in high rise buildings.…”

Section: Related Workmentioning

confidence: 99%

UGVs spotting fire location for Cooperative Fire Security System using HARMS

Gómez

Matson

Song

et al. 2015

2015 6th International Conference on Automation, Robotics and Applications (ICARA)

View full text Add to dashboard Cite

Recent trends are to build tall buildings in big cities as a way out of the current housing overpopulation problem. These new structures unveil problems that if not addressed in time could cause catastrophes of unimaginable impact. One of those problems is the incidence of a fire threat happening upstairs in one of those buildings. Research solutions include implementation of multi-agent fire safety systems for fire threats in high rise buildings. Humans, agents, robots, machines and sensors communication model is used for indistinguishability of actors. This work discusses the implementation of the unmanned ground vehicles to spot the real location of the fire.

show abstract

“…In large scale industrial infrastructures there are afforded many opportunities for the application of autonomous systems to take over dull or menial jobs otherwise done by humans. In [23] a multi-robot system for building maintenance and surveillance was demonstrated, with advantages of increased efficiency and reducing manpower. Here mobile robots are able to roam throughout the building and collect information through the use of RFID tags on monitored equipment and feed this information to a central management centre.…”

Section: Automation Within Industrial Maintenancementioning

confidence: 99%

Autonomous Maintenance for Through-Life Engineering

Farnsworth

Bell

Khan

et al. 2014

Decision Engineering

View full text Add to dashboard Cite

This chapter looks at the overall theme of automating maintenance practices with a particular focus upon the application of robotics within this field. Covering the current state of the art in automating maintenance processes this chapter also looks at the current challenges to moving beyond simple inspection and diagnosis to the design and construction of fully automated platforms for undertaking maintenance. This includes methodologies for capturing and classifying maintenance task processes so that they can be automated in some way and how to link this task classification with some level of automation. The chapter ends with a discussion on how the design process can be adapted to aid automated maintenance, self-healing and no fault found applications.

show abstract

WatchBot: A building maintenance and surveillance system based on autonomous robots

Cited by 49 publications

References 17 publications

Learning fuzzy controllers in mobile robotics with embedded preprocessing

Learning fuzzy controllers in mobile robotics with embedded preprocessing

UGVs spotting fire location for Cooperative Fire Security System using HARMS

Autonomous Maintenance for Through-Life Engineering

Contact Info

Product

Resources

About