Demo Data from SIGIR 2026 / reviewers in the wild / expert
Eranda Tennakoon
dblp:241/2397
· DBLP profile ↗
1ranked-venue papers
1as 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 · 1 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
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 · 88% Motion planning and robot control · 12% |
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 › legged robots
multi-legged robot |
0.4 | 1 | 2020 | Probe-before-step walking strategy for multi-legged robots on terrain with risk of collapse · ICRA 2020 |
Robotics › Legged, aerial and field robots
rough terrain locomotion |
0.4 | 1 | 2020 | Probe-before-step walking strategy for multi-legged robots on terrain with risk of collapse · ICRA 2020 |
Robotics › Motion planning and robot control › multi-robot control
follow-the-leader deployment |
0.1 | 1 | 2020 | Probe-before-step walking strategy for multi-legged robots on terrain with risk of collapse · ICRA 2020 |
Robotics › Legged, aerial and field robots › legged robots › legged robot locomotion
gait planning |
0.1 | 1 | 2020 | Probe-before-step walking strategy for multi-legged robots on terrain with risk of collapse · ICRA 2020 |
Methods — techniques the papers use, named apart from their topics
terrain probing · 0.4gait and stance design · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Probe-before-step walking strategy for multi-legged robots on terrain with risk of collapseabstractMulti-legged robots are effective at traversing rough terrain. However, terrains that include collapsible footholds (i.e. regions that can collapse when stepped on) remain a significant challenge, especially since such situations can be extremely difficult to anticipate using only exteroceptive sensing. State-of-the-art methods typically use various stabilisation techniques to regain balance and counter changing footholds. However, these methods are likely to fail if safe footholds are sparse and spread out or if the robot does not respond quickly enough after a foothold collapse. This paper presents a novel method for multi-legged robots to probe and test the terrain for collapses using its legs while walking. The proposed method improves on existing terrain probing approaches, and integrates the probing action into a walking cycle. A follow-the-leader strategy with a suitable gait and stance is presented and implemented on a hexapod robot. The proposed method is experimentally validated, demonstrating the robot can safely traverse terrain containing collapsible footholds. Eranda Tennakoon, Thierry Peynot, Jonathan Roberts 0001, Navinda Kottege |
ICRA | 1 |