Samuel Coogan

About

Samuel Coogan is a robotics and control systems researcher whose work sits at the intersection of formal methods, safety-critical control, and multi-agent systems. He is best known for his foundational contributions to **control barrier functions (CBFs)**, a mathematical framework for guaranteeing safety in dynamical systems. His 2019 survey, "Control Barrier Functions: Theory and Applications," has become an essential reference in the field with 78 citations, while his work on finite-time convergence CBFs for multi-agent systems (85 citations) demonstrates how temporal logic specifications can be systematically translated into provably safe controllers. Coogan's research extends across multi-robot task allocation, where he applies cross-entropy optimization and linear temporal logic to coordinate robot teams, and uncertainty-aware planning, where interval Markov decision processes provide rigorous probabilistic safety guarantees for systems ranging from legged robots to aerial swarms. His 2022 work on safe learning under uncertainty reflects a growing focus on bridging data-driven methods with formal verification. Additional contributions to distributed field mapping, heterogeneous agent coordination, and extent-compatible barrier functions reveal the breadth of his portfolio. With over 250 cumulative citations, Coogan has established himself as a significant voice in safe autonomy and multi-robot systems research.

Research Focus

Key Achievements

Top Papers

1. 1
   Control of Multi-Agent Systems with Finite Time Control Barrier Certificates and Temporal Logic

   85 citations · 2018
2. 2
   Control Barrier Functions: Theory and Applications

   78 citations · 2019
3. 3
   Multi-Agent Task Allocation using Cross-Entropy Temporal Logic Optimization

   24 citations · 2020
4. 4
   Safe Learning for Uncertainty-Aware Planning via Interval MDP Abstraction

   16 citations · 2022
5. 5
   Extent-compatible control barrier functions

   14 citations · 2021
6. 6
   A Distributed Scalar Field Mapping Strategy for Mobile Robots

   9 citations · 2020
7. 7
   Weighted Polar Finite Time Control Barrier Functions With Applications To Multi-Robot Systems

   8 citations · 2019
8. 8
   Leveraging Heterogeneous Capabilities in Multi-Agent Systems for Environmental Conflict Resolution

   7 citations · 2022
9. 9
   Area Coverage Using Multiple Aerial Robots With Coverage Redundancy and Collision Avoidance

   6 citations · 2024
10. 10
    Abstraction-Based Planning for Uncertainty-Aware Legged Navigation

    6 citations · 2023

Key Collaborators

Contact & Links