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Rajesh Mahtani

dblp:08/3021 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1Systems, architecture and hardware · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
1 paper
Legged, aerial and field robots · 50% Robot navigation and mapping · 50%
Computer architecture, parallel and distributed computing, and storage systems
1 paper
Electronic design automation · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Legged, aerial and field robots › aerial robots
autonomous helicopter		 0.112005
Detection of Sensor Faults in Autonomous Helicopters · ICRA 2005
Robotics › Robot navigation and mapping › fault detection
sensor fault detection		 0.112005
Detection of Sensor Faults in Autonomous Helicopters · ICRA 2005
Electronic design automation › hardware verification and test
fault diagnosis		 0.012005
Detection of Sensor Faults in Autonomous Helicopters · ICRA 2005

Methods — techniques the papers use, named apart from their topics

observer-based detection · 0.1
YearPublicationVenuePosition
2005 Detection of Sensor Faults in Autonomous Helicopters
abstract
This paper presents a sensor fault detection and diagnosis system for autonomous helicopters. The system has been tested with the MARVIN autonomous helicopter. Fault detection is accomplished by evaluating any significant change in the behaviour of the vehicle with respect to the fault-free behaviour, which is estimated by using an observer. The effectiveness of the proposed approach is demonstrated by means of MARVIN experimental results.
Guillermo Heredia, Aníbal Ollero, Rajesh Mahtani, Manuel Béjar, Volker Remuß, Marek Musial
 ICRA3