Patricia Sheridan

University of Toronto

Papers

2

Total Citations

19

H-Index

2

About

Patricia Sheridan’s research lies at the intersection of autonomous navigation and multi-robot coordination, with a focus on enabling robots to intercept agile, unpredictable targets in dynamic environments. Her seminal work, “Predictive Guidance-Based Navigation for Mobile Robots” (2010, 14 citations), introduces a novel strategy for target interception on realistic terrains, blending predictive modeling with real-time guidance to overcome the challenges of uneven or obstructed landscapes. This contribution is foundational for applications in surveillance, search-and-rescue, and autonomous defense systems. Expanding on this, her paper “On-line task allocation for the robotic interception of multiple targets in dynamic settings” (2010, 5 citations) presents an innovative rolling-horizon optimization methodology that allows a team of robotic pursuers to dynamically assign tasks and intercept highly maneuverable targets. By increasing the depth of online search, this work enhances the efficiency and adaptability of multi-agent systems under time-critical conditions. Though her citation counts are modest, Sheridan’s contributions are notable for their practical rigor and forward-thinking approach, providing a blueprint for real-world autonomous systems that must operate in unpredictable, high-stakes scenarios. Her research continues to inspire advancements in robotics and artificial intelligence.

Research Focus

Key Achievements

2
H-Index
2
Papers
19
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Predictive Guidance-Based Navigation for Mobile Robots: A Novel Strategy for Target Interception on Realistic Terrains
14 citations · 2010
📈 Most Prolific Year: 2010 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of Toronto

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago