Glen Neville
Papers
6
Total Citations
111
H-Index
5
About
Glen Neville’s research lies at the critical intersection of multi-robot coordination and human-robot interaction, addressing fundamental challenges in deploying effective, trustworthy autonomous teams. His most impactful work, “GRSTAPS,” introduces a novel, graphically recursive framework that simultaneously solves task allocation, planning, and scheduling for heterogeneous multi-robot systems—a problem he describes as answering *what*, *how*, *who*, and *when*. This work has garnered 35 citations and established a foundation for resilient coordination. Neville further advanced this line with “D-ITAGS,” a dynamic interleaved approach that maintains mission resilience in the face of sensor failures and communication loss (23 citations). Recognizing that technical capability alone is insufficient, Neville’s highly cited study on human trust (29 citations) explores how different forms of robot communication following mistakes can either repair or further degrade user trust—a critical insight for collaborative robots. His work on trait-based task allocation leverages individual robot strengths for more effective teaming, while his investigation into social factors and team dynamics (8 citations) directly addresses worker apprehension toward automation. Through this dual focus on algorithmic coordination and human-centered design, Neville is shaping a future where multi-robot teams are both highly capable and genuinely trusted by their human collaborators.
Research Focus
Key Achievements
Top Papers
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- 4An Interleaved Approach to Trait-Based Task Allocation and Scheduling14 citations · 2021
- 5
- 6Approximated Dynamic Trait Models for Heterogeneous Multi-Robot Teams2 citations · 2020