Swarat Chaudhuri

About

Swarat Chaudhuri is a robotics and artificial intelligence researcher whose work sits at the intersection of automated planning, formal methods, and robot autonomy. He is perhaps best known for his foundational contributions to **task and motion planning (TMP)**, an area concerned with enabling robots to seamlessly bridge high-level symbolic reasoning with continuous physical motion. His landmark algorithm, Iteratively Deepened Task and Motion Planning (IDTMP), introduced an incremental constraint-based framework that is both probabilistically complete and broadly generalizable, garnering over 290 combined citations across its 2016 and 2018 iterations. His 2014 work on SMT-based synthesis further demonstrated his aptitude for applying formal verification techniques to mobile manipulation challenges. Beyond planning, Chaudhuri has made significant contributions to policy synthesis under uncertainty, tackling Partially Observable Markov Decision Processes (POMDPs) with safety guarantees and liveness objectives for dynamic environments. His open-source Task-Motion Kit has lowered barriers for the broader robotics community. More recently, his research has extended into distributed robotic control and complex motor action planning, reflecting a consistently expanding research vision aimed at building truly autonomous, reliable robotic systems.

Research Focus

Key Achievements

Top Papers

1. 1
   Incremental Task and Motion Planning: A Constraint-Based Approach

   168 citations · 2016
2. 2
   An incremental constraint-based framework for task and motion planning

   124 citations · 2018
3. 3
   SMT-based synthesis of integrated task and motion plans from plan outlines

   62 citations · 2014
4. 4
   The Task-Motion Kit: An Open Source, General-Purpose Task and Motion-Planning Framework

   42 citations · 2018
5. 5
   Task and Motion Policy Synthesis as Liveness Games

   24 citations · 2016
6. 6
   Bounded Policy Synthesis for POMDPs with Safe-Reachability Objectives

   18 citations · 2018
7. 7
   Bounded Policy Synthesis for POMDPs with Safe-Reachability Objectives

   10 citations · 2018
8. 8
   A Sampling-based Motion Planning Framework for Complex Motor Actions

   6 citations · 2021
9. 9
   OneVision: Centralized to Distributed Controller Synthesis with Delay Compensation

   4 citations · 2021
10. 10
    Point-Based Policy Synthesis for POMDPs With Boolean and Quantitative Objectives

    3 citations · 2019

Key Collaborators

Contact & Links