Charles Pippin

About

Charles Pippin is a robotics researcher whose work centers on multi-robot systems, autonomous navigation, and intelligent task allocation. He has made significant contributions to the field of multi-robot patrolling, developing novel approaches to one of robotics' most practically relevant challenges: efficiently coordinating robot teams for surveillance and security applications. His 2013 paper on performance-based task assignment (47 citations) and his 2014 work on optimal routing strategies (40 citations) established foundational methods for distributing patrol responsibilities among robot teams, tackling the NP-hard complexity inherent in such coordination problems. Beyond patrolling, Pippin has advanced the field through his work on trust modeling in multi-robot teams (34 citations), recognizing that robot reliability is a critical and often overlooked variable in cooperative systems. His bio-inspired research on communication through behavior recognition offers an elegant alternative to traditional radio-based coordination, drawing on biological analogies to enable implicit robot-to-robot understanding. His 2008 work on cost-based RRT planning (38 citations) extended classical path-planning algorithms for real-world outdoor environments. With a cumulative body of work exceeding 240 citations, Pippin's research consistently bridges theoretical rigor with practical robotics applications, including UAV teams, underwater vehicles, and large-scale simulation environments like SCRIMMAGE.

Research Focus

Key Achievements

Top Papers

1. 1
   Performance based task assignment in multi-robot patrolling

   47 citations · 2013
2. 2
   Finding optimal routes for multi-robot patrolling in generic graphs

   40 citations · 2014
3. 3
   Cost based planning with RRT in outdoor environments

   38 citations · 2008
4. 4
   Trust modeling in multi-robot patrolling

   34 citations · 2014
5. 5
   Simulating Collaborative Robots in a Massive Multi-agent Game Environment (SCRIMMAGE)

   22 citations · 2019
6. 6
   Bio-inspired multi-robot communication through behavior recognition

   18 citations · 2012
7. 7
   A Bayesian formulation for auction-based task allocation in heterogeneous multi-agent teams

   16 citations · 2011
8. 8
   Dynamic, cooperative multi-robot patrolling with a team of UAVs

   14 citations · 2013
9. 9
   Bio-inspired Role Allocation of Heterogeneous Teams in a Site Defense Task

   8 citations · 2019
10. 10
    AUV behavior recognition using behavior histograms, HMMs, and CRFs

    4 citations · 2014

Key Collaborators

Contact & Links