Demo Data from EDBT 2026 / reviewers in the wild / expert
Raihan Enjikalayil Abdulkader
dblp:267/6186
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0001-6538-4875ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 since 2021Systems, architecture and hardware · 2 · 1 since 2021
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 |
Motion planning and robot control · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Personal fabrication and tangible interfaces · 100% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Motion planning and robot control › path planning
coverage path planning |
0.8 | 1 | 2024 | Toward Mass Customization of a Robot's Morphology Design for Improving Area Coverage · ICRA 2024 |
Methods — techniques the papers use, named apart from their topics
surrogate optimization · 1.5particle swarm optimization · 1.5generalized pattern search · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Toward Mass Customization of a Robot's Morphology Design for Improving Area CoverageabstractFloor cleaning robots have been developed to cater to building maintenance needs. Complete area coverage is crucial for a floor cleaning robot, and its morphology design plays a vital role in realizing complete area coverage. However, floor cleaning robots with fixed morphologies have difficulty in achieving a high area coverage performance. Mass customization of a robot’s morphology would improve its productivity in terms of area coverage. This paper proposes a novel system that can be used for mass customizing the morphology of a robot to improve area coverage performance in an environment of interest. The customized morphology is determined through an optimization technique by considering an environment of interest and design constraints. The area coverage of a candidate morphology design is evaluated by simulating the robot navigation in an environment of interest. Generalized pattern search, particle swarm optimization, and surrogate optimization are independently considered optimization techniques. Experiments have been conducted considering the cases of robot deployments. The statistical conclusions on experimental results validate that the proposed system can synthesize a morphology that significantly improves the area coverage performance in an environment of interest. M. A. Viraj J. Muthugala, S. M. Bhagya P. Samarakoon, Raihan Enjikalayil Abdulkader, Mohan Rajesh Elara |
ICRA | 3 |
| 2020 | Ospheel: Design of an Omnidirectional Spherical-sectioned WheelabstractThe holonomic and omnidirectional capabilities imparted to the mobile base platform depends mainly on two factors, i.e., the wheel design and its various arrangements in the platform chassis. This paper reports on the development of a novel omnidirectional spherical sectioned wheel named Ospheel. It is modular, and the spherical sectioned geometry of the wheel is driven using two actuators placed inside the housing above the wheel that rotates it independently about two perpendicular axes. The mechanical drive system for Ospheel consists of two gear trains, namely, internal spur gear and crown gear spatially assembled in orthogonal planes and are driven by two driving pinions. The kinematics of a single Ospheel is described, followed by the kinematic equation of a robot equipped with two Ospheels. Forward and inverse kinematic equations are derived explicitly. Experiments were carried out with the two Ospheels at a fixed inclination assembled with the base to illustrate the holonomic motion. The robustness of the wheel design is experimented with different trajectories and on different terrains. Abdullah Aamir Hayat, Yuyao Shi, Karthikeyan Elangovan, Mohan Rajesh Elara, Raihan Enjikalayil Abdulkader |
IROS | 5 |