Demo Data from VLDB 2026 / reviewers in the wild / expert
Pravin Dangol
dblp:264/0164
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 since 2021Systems, architecture and hardware · 1 · 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 |
Legged, aerial and field robots · 100% | |
| Theoretical computer science
1 paper |
Mathematical optimization · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
aerial robots |
0.5 | 1 | 2021 | Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged Robot · ICRA 2021 |
Robotics › Legged, aerial and field robots
legged robots |
0.5 | 1 | 2021 | Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged Robot · ICRA 2021 |
Mathematical optimization
design optimization |
0.1 | 1 | 2021 | Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged Robot · ICRA 2021 |
Mathematical optimization › design optimization
generative design |
0.1 | 1 | 2021 | Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged Robot · ICRA 2021 |
Methods — techniques the papers use, named apart from their topics
parametric design space search · 1.0evolutionary solver · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | Generative Design of NU's Husky Carbon, A Morpho-Functional, Legged RobotabstractWe report the design of a morpho-functional robot called Husky Carbon. Our goal is to integrate two forms of mobility, aerial and quadrupedal legged locomotion, within a single platform. There are prohibitive design restrictions such as tight power budget and payload, which can particularly become important in aerial flights. To address these challenges, we pose a problem called the Mobility Value of Added Mass (MVAM) problem. In the MVAM problem, we attempt to allocate mass in our designs such that the energetic performance is affected the least. To solve the MVAM problem, we adopted a generative design approach using Grasshopper’s evolutionary solver to synthesize a parametric design space for Husky. Then, this space was searched for the morphologies that could yield a minimized Total Cost Of Transport (TCOT) and payload. This approach revealed that a front heavy quadrupedal robot can achieve a lower TCOT while retaining larger margins on allowable added mass to its design. Based on this framework Husky was built and tested as a front heavy robot. Alireza Ramezani, Pravin Dangol, Eric Sihite, Andrew Lessieur, Peter Kelly |
ICRA | 2 |