Kadir Haspalamutgil

About

Kadir Haspalamutgil’s research lies at the intersection of artificial intelligence and robotics, focusing on bridging the gap between high-level reasoning and low-level control. His major contribution is a formal framework that integrates causality-based task planning with geometric reasoning and motion planning for robotic manipulation. This work, detailed in his most-cited paper (126 citations), enables robots to reason about actions and their effects while simultaneously computing feasible physical motions, allowing for bilateral interaction between symbolic and geometric layers. Haspalamutgil further demonstrated this integration through the classic Tower of Hanoi challenge (33 citations), establishing it as a benchmark for evaluating cognitive robotic systems. His research extends to cognitive factories, where he applies causality-based planning and diagnostic reasoning to coordinate multi-robot teams (20 citations). By embedding geometric constraints directly into causal reasoning, Haspalamutgil has advanced the development of robots capable of both abstract thought and precise physical execution, making his work foundational for researchers in task-and-motion planning and autonomous manipulation.

Research Focus

Key Achievements

Top Papers

1. 1
   Combining high-level causal reasoning with low-level geometric reasoning and motion planning for robotic manipulation

   126 citations · 2011
2. 2
   Bridging the Gap between High-Level Reasoning and Low-Level Control

   38 citations · 2009
3. 3
   A case study on the Tower of Hanoi challenge: Representation, reasoning and execution

   33 citations · 2013
4. 4
   Causality-based planning and diagnostic reasoning for cognitive factories

   20 citations · 2012
5. 5
   From discrete task plans to continuous trajectories

   5 citations · 2009
6. 6
   A tight integration of task planning and motion planning in an execution monitoring framework

   2 citations · 2010

Key Collaborators

Contact & Links