Demo Data from SIGIR 2026 / reviewers in the wild / expert
Ruchita Vucha
dblp:249/5658 · also Ruchitha Vucha
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—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 |
Robot navigation and mapping · 44% Legged, aerial and field robots · 44% Motion planning and robot control · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Robot navigation and mapping › mobile robot navigation
in-pipe navigation |
0.4 | 1 | 2020 | Omnidirectional Tractable Three Module Robot · ICRA 2020 |
Robotics › Legged, aerial and field robots › wheeled mobile robot
omni-directional robot |
0.4 | 1 | 2020 | Omnidirectional Tractable Three Module Robot · ICRA 2020 |
Methods — techniques the papers use, named apart from their topics
kinematic modeling · 0.4dynamics simulation · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Omnidirectional Tractable Three Module RobotabstractThis paper introduces the Omnidirectional Tractable Three Module Robot for traversing inside complex pipe networks. The robot consists of three omnidirectional modules fixed 120° apart circumferentially which can rotate about their own axis allowing holonomic motion of the robot. The holonomic motion enables the robot to overcome motion singularity when negotiating T-junctions and further allows the robot to arrive in a preferred orientation while taking turns inside a pipe. We have developed a closed-form kinematic model for the robot in the paper and propose the `Motion Singularity Region' that the robot needs to avoid while negotiating T-junction. The design and motion capabilities of the robot are demonstrated both by conducting simulations in MSC ADAMS on a simplified lumped-model of the robot and with experiments on its physical embodiment. Kartik Suryavanshi, Rama Vadapalli, Ruchita Vucha, K. Madhava Krishna |
ICRA | 3 |