Pablo Gruer

About

Pablo Gruer is a leading researcher in multi-agent systems and autonomous vehicle control, with a focus on vehicle platooning and obstacle avoidance. His work centers on developing reactive agent-based algorithms that enable vehicles to maintain coordinated formations—such as platoons—while dynamically responding to obstacles and trajectory changes. Gruer’s major contributions include pioneering a physics-inspired multi-agent system for vehicle platooning (2007, 11 citations) and a reactive agent approach that integrates platoon control with obstacle avoidance (2013, 28 citations), demonstrating how simple, decentralized agents can solve complex navigation problems. His research has been validated through real-world experiments, including tests on a robot-soccer platform for reference-path control (2008, 3 citations). Gruer has also explored self-adaptive lateral regulation and immune-based agent architectures, broadening the theoretical foundations of autonomous systems. With over 60 citations across his most-cited works, his impact is evident in advancing scalable, decentralized control methods for intelligent transportation. His achievements highlight the practical power of reactive multi-agent systems in shaping the future of autonomous driving.

Research Focus

Key Achievements

Top Papers

1. 1
   Vehicle platoon and obstacle avoidance: a reactive agent approach

   28 citations · 2013
2. 2
   A Reactive Agent Based Vehicle Platoon Algorithm with Integrated Obstacle Avoidance Ability

   11 citations · 2011
3. 3
   Physics inspired multiagent system for vehicle platooning

   11 citations · 2007
4. 4
   A self-adaptive agent-based path following control lateral regulation and obstacles avoidance

   6 citations · 2014
5. 5
   THE APPLICATION OF REFERENCE-PATH CONTROL TO VEHICLE PLATOONS

   3 citations · 2008
6. 6
   Formal specification of an immune based agent architecture

   3 citations · 2010

Key Collaborators

Contact & Links