Rahul Kala

About

Rahul Kala is a prominent researcher in robotics and artificial intelligence, with a career defined by pioneering contributions to robotic path planning, autonomous navigation, and multi-robot coordination. His work has consistently explored the intersection of classical search algorithms and soft computing techniques, developing innovative hybrid approaches that address complex real-world challenges in mobile robotics. Kala's most influential contributions include his fusion of probabilistic A* algorithms with fuzzy inference systems for path planning (144 citations) and his application of co-evolutionary genetic programming to multi-robot coordination (124 citations), establishing him as a leading voice in intelligent robotic navigation. His research spans static and dynamic environments, incorporating genetic algorithms, artificial neural networks, hierarchical evolutionary algorithms, and sampling-based methods like his novel rapidly exploring random graphs framework. His 2012 book, *Intelligent Planning for Mobile Robotics: Algorithmic Approaches*, consolidates much of this foundational thinking into a comprehensive academic resource. More recently, Kala has expanded his scope to socially aware autonomous navigation, examining how robots can interpret and respond to human social cues in indoor environments. With hundreds of citations across his portfolio and contributions spanning algorithms, coordination theory, and applied AI, Kala's work has substantially shaped modern autonomous robotics research.

Research Focus

Key Achievements

Top Papers

1. 1
   Fusion of probabilistic A* algorithm and fuzzy inference system for robotic path planning

   144 citations · 2010
2. 2
   Multi-robot path planning using co-evolutionary genetic programming

   124 citations · 2011
3. 3
   Robotic path planning in static environment using hierarchical multi-neuron heuristic search and probability based fitness

   58 citations · 2011
4. 4
   Mobile Robot Navigation Control in Moving Obstacle Environment Using Genetic Algorithm, Artificial Neural Networks and A* Algorithm

   53 citations · 2009
5. 5
   Rapidly exploring random graphs: motion planning of multiple mobile robots

   46 citations · 2013
6. 6
   DYNAMIC ENVIRONMENT ROBOT PATH PLANNING USING HIERARCHICAL EVOLUTIONARY ALGORITHMS

   46 citations · 2010
7. 7
   Intelligent Planning for Mobile Robotics: Algorithmic Approaches

   39 citations · 2012
8. 8
   Social Cues in the Autonomous Navigation of Indoor Mobile Robots

   33 citations · 2020
9. 9
   Coordination in Navigation of Multiple Mobile Robots

   26 citations · 2014
10. 10
    Robotic path planning using evolutionary momentum-based exploration

    24 citations · 2011

Key Collaborators

Contact & Links