Demo Data from SIGIR 2026 / reviewers in the wild / expert
Masazumi Imai
dblp:338/7199
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2023
—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 · 72% Motion planning and robot control · 28% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
legged robots |
0.7 | 1 | 2023 | RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity · ICRA 2023 |
Robotics › Motion planning and robot control
motion planning |
0.7 | 1 | 2023 | RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity · ICRA 2023 |
Robotics › Legged, aerial and field robots › legged robots
multi-legged robot |
0.7 | 1 | 2023 | RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity · ICRA 2023 |
Robotics › Legged, aerial and field robots › space robotics
microgravity locomotion |
0.2 | 1 | 2023 | RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity · ICRA 2023 |
Robotics › Legged, aerial and field robots
space robotics |
0.2 | 1 | 2023 | RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity · ICRA 2023 |
Methods — techniques the papers use, named apart from their topics
low-reaction swing trajectory · 0.7dynamic simulation · 0.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in MicrogravityabstractRobotic mobility in microgravity is necessary to expand human utilization and exploration of outer space. Bio-inspired multi-legged robots are a possible solution for safe and precise locomotion. However, a dynamic motion of a robot in microgravity can lead to failures due to gripper detachment caused by excessive motion reactions. We propose a novel Reaction-Aware Motion Planning (RAMP) to improve locomotion safety in microgravity, decreasing the risk of losing contact with the terrain surface by reducing the robot's momentum change. RAMP minimizes the swing momentum with a Low-Reaction Swing Trajectory (LRST) while distributing this momentum to the whole body, ensuring zero velocity for the supporting grippers and minimizing motion reactions. We verify the proposed approach with dynamic simulations indicating the capability of RAMP to generate a safe motion without detachment of the supporting grippers, resulting in the robot reaching its specified location. We further validate RAMP in experiments with an air-floating system, demonstrating a significant reduction in reaction forces and improved mobility in microgravity. Warley F. R. Ribeiro, Kentaro Uno, Masazumi Imai, Koki Murase, Kazuya Yoshida |
ICRA | 3 |