Prateek Asthana

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VLDB 2026 Research / reviewers in the wild / expert

dblp:07/7495 · DBLP profile ↗

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2ranked-venue papers

0as first author

0since 2021 · last 2007

—ORCID · none

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

Artificial intelligence and machine learning · 2Systems, architecture and hardware · 2

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

2 papers

Legged, aerial and field robots · 25% Robot navigation and mapping · 25% Motion planning and robot control · 25%

Topics — the 4 heaviest of 4, each with the papers that count most for it

Topic	Weight	Papers	Last	Evidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › diagnosis model-based diagnosis	0.1	2	2007	Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II) · ICRA 2007 Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Theoretical Aspects (part I) · ICRA 2007
Robotics › Motion planning and robot control robot control	0.1	2	2007	Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II) · ICRA 2007 Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Theoretical Aspects (part I) · ICRA 2007
Robotics › Robot navigation and mapping › fault detection sensor fault detection	0.1	2	2007	Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II) · ICRA 2007 Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Theoretical Aspects (part I) · ICRA 2007
Robotics › Legged, aerial and field robots unmanned ground vehicle	0.1	2	2007	Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II) · ICRA 2007 Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Theoretical Aspects (part I) · ICRA 2007

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

structural analysis · 0.1residual generation · 0.1residual evaluation · 0.1

Year	Publication	Venue	Position
2007	Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Theoretical Aspects (part I) abstract This paper presents theoretical details of a model-based sensor fault detection and isolation system (SFDIS) applied to unmanned ground vehicles (UGVs). Structural analysis is applied to the nonlinear model of the vehicle for residual generation. Two different solutions have been proposed for developing the residual evaluation module. The vehicle sensor suite includes a global positioning system (GPS) antenna, an inertial measurement unit (IMU), and two incremental optical encoders. Andrea Monteriù, Prateek Asthana, Kimon P. Valavanis, Sauro Longhi	ICRA	2
2007	Model-Based Sensor Fault Detection and Isolation System for Unmanned Ground Vehicles: Experimental Validation (part II) abstract This paper presents implementation details of a model-based sensor fault detection and isolation system (SFDIS) applied to unmanned ground vehicles (UGVs). Structural analysis, applied to the nonlinear model of the UGV, is followed to build the residual generation module, followed by a residual evaluation module capable of detecting single and multiple sensor faults, as detailed in part I (Monteriu et al., 2007). The overall proposed sensor fault detection and isolation system has been tested in real-time on the ATRV-Jr mobile robot when following different trajectories in an outdoors environment. The robot sensor suite includes a global positioning system (GPS) antenna, an inertial measurement unit (IMU), and two incremental optical encoders Andrea Monteriù, Prateek Asthana, Kimon P. Valavanis, Sauro Longhi	ICRA	2