Demo Data from SIGIR 2026 / reviewers in the wild / expert
Max Polzin
dblp:203/5254
· DBLP profile ↗
2ranked-venue papers
1as first author
1since 2021 · last 2023
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 2 · 1 first-author · 1 since 2021Systems, architecture and hardware · 2 · 1 first-author · 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
2 papers |
Motion planning and robot control · 43% Legged, aerial and field robots · 40% Robot navigation and mapping · 17% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Robotics › Legged, aerial and field robots
aerial robots |
0.7 | 1 | 2023 | Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot · ICRA 2023 |
Robotics › Motion planning and robot control › robot control
controller design |
0.7 | 1 | 2023 | Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot · ICRA 2023 |
Robotics › Motion planning and robot control › robot control › feedback control
PD control |
0.7 | 1 | 2023 | Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot · ICRA 2023 |
Robotics › Legged, aerial and field robots › aerial robots › unmanned aerial vehicle
tethered aerial robot |
0.7 | 1 | 2023 | Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial Robot · ICRA 2023 |
Robotics › Robot navigation and mapping › mobile robot navigation › route navigation
teach-and-repeat navigation |
0.3 | 1 | 2017 | Falling in line: Visual route following on extreme terrain for a tethered mobile robot · ICRA 2017 |
Robotics › Robot navigation and mapping › visual navigation
visual path following |
0.3 | 1 | 2017 | Falling in line: Visual route following on extreme terrain for a tethered mobile robot · ICRA 2017 |
Robotics › Motion planning and robot control
robot control |
0.1 | 1 | 2017 | Falling in line: Visual route following on extreme terrain for a tethered mobile robot · ICRA 2017 |
Methods — techniques the papers use, named apart from their topics
spherical pendulum model · 0.7bang-bang control · 0.7visual teach and repeat · 0.3tether controller · 0.3
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Heading for the Abyss: Control Strategies for Exploiting Swinging of a Descending Tethered Aerial RobotabstractThe use of aerial vehicles for exploration and data collection has the potential to significantly aid environmental monitoring in environments which are dangerous and hard to navigate. However, within these environments navigation can often be restricted by overhangs which are challenging to navigate, particularly so with the high payloads required for environmental monitoring. We propose utilizing a tethered bicopter with horizontal propellers. This spherical pendulum like system can exploit the tether, not only as a means of powering and recovering the robot, but also to assist its motion, i.e. by swinging to increase the workspace of the robot. Using PD-based control, we demonstrate how the system can be stabilized and bang-bang control to excite the system to achieve large amplitude swinging. By combining these controllers, we show how the system can be used to navigate in a glacial-inspired scenario where there are overhangs and obstacles through which the robot must navigate. Max Polzin, Frank Centamori, Josie Hughes |
ICRA | 1 |
| 2017 | Falling in line: Visual route following on extreme terrain for a tethered mobile robotabstractThis paper describes visual route following for a cliff-climbing, tethered mobile robot for the purpose of autonomously traversing extreme terrain in the presence of obstacles. When the robot's tether contacts an obstacle, an intermediate anchor is formed. In order to detach from intermediate anchors and avoid entanglement, the robot must backtrack along its outgoing trajectory. We use the Visual Teach & Repeat (VT&R) algorithm to autonomously repeat a manually taught path. However, our problem is complicated by the fact that the robot's tether must (i) remain taut regardless of inclination, (ii) allow the robot to drive freely, and (iii) provide motion assistance when wheel traction is reduced on steep slopes. To enable visual route following over varied terrain, we have developed a novel tether controller that selects a safe, steady-state tension based on the robot's inclination while also accounting for vehicle motion. Experiments are performed on our Tethered Robotic Explorer (TReX), which autonomously repeats paths while tethered in both flat-indoor and steep-outdoor environments in the presence of obstacles. Patrick McGarey, Max Polzin, Tim D. Barfoot |
ICRA | 2 |