Demo Data from VLDB 2026 / reviewers in the wild / expert
Tyler Errico
dblp:376/9001
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
—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.
| Human-computer interaction and pervasive computing
1 paper |
Human-robot interaction · 77% Usability and user experience research · 23% | |
| Artificial intelligence
1 paper |
Multi-agent systems · 100% |
Topics — the 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Knowledge, reasoning and agents › Multi-agent systems
multi-robot coordination |
0.9 | 1 | 2025 | Integrating Human-Robot Teaming Dynamics Into Mission Planning Tools for Transparent Tactics in Multi-Robot Human Integrated Teams · ICRA 2025 |
Human-robot interaction › multi-robot systems
multi-robot teams |
0.9 | 1 | 2025 | Integrating Human-Robot Teaming Dynamics Into Mission Planning Tools for Transparent Tactics in Multi-Robot Human Integrated Teams · ICRA 2025 |
Usability and user experience research
cognitive load |
0.3 | 1 | 2025 | Integrating Human-Robot Teaming Dynamics Into Mission Planning Tools for Transparent Tactics in Multi-Robot Human Integrated Teams · ICRA 2025 |
Methods — techniques the papers use, named apart from their topics
mission planning tools · 1.7
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Integrating Human-Robot Teaming Dynamics Into Mission Planning Tools for Transparent Tactics in Multi-Robot Human Integrated TeamsabstractThis research aims to demonstrate how integrating human-robot teaming dynamics into mission planning tools impacts the abilities of robot operators as they coordinate multiple robot agents during a mission. This was investigated in a pilot study using two inter-robot collaboration modalities and interface tools, which required different human-robot interaction techniques to execute a mission with a team of four robots. In the first modality, the operator manually inserted waypoints for each robot, as they acted as individual agents. In the second modality, the operator used the Planning Execution to After-Action Review (PETAAR) toolset to plot a single waypoint for the team of robots, as the robots coordinated their movement as a group. One novel component of this study is the investigation of how human-robot teaming dynamics and the PETAAR toolset impacted robot operators' real-time situation awareness and perceived cognitive load as well as team performance. Although the teaming modalities differed greatly with respect to the level of operator input needed, the time required to complete the simulation, the participant's perceived cognitive load, and interface usability were very similar for both modalities. In contrast, the results revealed statistically significant differences between the two teaming modalities related to participants' abilities to maintain a wedge formation while remaining situationally aware. Results from this work will be used to guide development of PETAAR along with the design of future studies investigating more complex teaming scenarios and for creating a baseline for comparing future results. Audrey L. Aldridge, Tyler Errico, Mitchell Morrell, Cindy L. Bethel, John James, Christa M. Chewar, Michael Novitzky |
ICRA | 2 |