Eric Schneider
University of Liverpool, Hunter College, King's College London
Papers
10
Total Citations
96
H-Index
5
About
Eric Schneider is a robotics and multi-agent systems researcher whose work centers on multi-robot coordination, task allocation, and human-robot interaction. His most influential contribution, "Auction-Based Task Allocation for Multi-robot Teams in Dynamic Environments" (2015, 53 citations), established him as a notable voice in distributed task allocation strategies, demonstrating how market-inspired mechanisms can efficiently coordinate robot teams operating in unpredictable settings. This line of inquiry extends into real-world applications, most recently through his 2020 work applying market-based allocation to ambulance dispatch — a compelling bridge between robotics theory and emergency services. Schneider has also made meaningful contributions to human/multi-robot interaction through the HRTeam framework, which provides researchers with tools to study collaborative decision-making between human operators and robot teams. His cognitive architecture work, applying FORR to shared human-robot decision-making, reflects a sophisticated interest in how robots can meaningfully incorporate human judgment. Further research on communication quality and environmental parameters affecting team performance reveals a methodologically rigorous approach, combining physical and simulated experiments across diverse metrics. With over 90 cumulative citations, Schneider's body of work offers valuable foundations for researchers tackling coordination, adaptability, and collaboration in complex multi-robot systems.
Research Focus
Key Achievements
Top Papers
- 1Auction-Based Task Allocation for Multi-robot Teams in Dynamic Environments53 citations · 2015
- 2Evaluating Multi-Robot Teamwork in Parameterised Environments12 citations · 2016
- 3HRTeam: a framework to support research on human/multi-robot interaction7 citations · 2013
- 4
- 5Applying FORR to human/multi-robot teams5 citations · 2012
- 6
- 7Behaviour mining for collision avoidance in multi-robot systems3 citations · 2014
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- 9
- 10MRComm: Multi-Robot Communication Testbed2 citations · 2019