Zachary Kingston

Assistant Professor of Computer Science
(he/him)

I am an Assistant Professor in the Computer Science Department at Purdue University, where I lead the CoMMA Lab. I completed my master’s, doctoral, and postdoctoral studies with Dr. Lydia E. Kavraki in the Computer Science Department at Rice University in Houston, Texas, studying manifold-constrained motion planning and long-horizon multi-modal motion planning. Throughout my Ph.D. studies, I was funded by a NASA Space Technology Research Fellowship and worked with the Robonaut 2 team within the Software, Robotics, and Simulation Division at NASA Johnson Space Center.

I am an Associate Editor for IEEE Robotics and Automation Letters under Planning and Simulation and the current maintainer of the Open Motion Planning Library, an open-source library with standard implementations of state-of-the-art sampling-based motion planners.

My research interests broadly encompass algorithms, methods, and software for complex robots to make decisions and find feasible or optimal motions to achieve task objectives safely in the world. I am interested in techniques that generalize and apply to any robotic system, constraint, or environment and are fast, efficient, and easy to use within a broader system. I am also interested in the intersection between the theory and practice of robotics algorithms, finding where software engineering, hardware acceleration, and intelligent algorithm design can synergize to create a whole greater than the sum of its parts.


2024

  1. Abstract
    Perception-aware Planning for Robotics: Challenges and Opportunities
    In 40th Anniversary of the IEEE Conference on Robotics and Automation (ICRA@40)
  2. Collision-Affording Point Trees: SIMD-Amenable Nearest Neighbors for Fast Collision Checking
    In Robotics: Science and Systems
  3. Motions in Microseconds via Vectorized Sampling-Based Planning
    In IEEE International Conference on Robotics and Automation
  4. Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty
    In IEEE International Conference on Robotics and Automation
  5. Accelerating Long-Horizon Planning with Affordance-Directed Dynamic Grounding of Abstract Strategies
    In IEEE International Conference on Robotics and Automation
  6. Workshop
    Stochastic Implicit Neural Signed Distance Functions for Safe Motion Planning under Sensing Uncertainty
    In IEEE ICRA 2024 Workshop—Back to the Future: Robot Learning Going Probabilistic
  7. Workshop
    Dynamic Motion Planning from Perception via Accelerated Point Cloud Collision Checking
    In IEEE ICRA 2024 Workshop—Agile Robotics: From Perception to Dynamic Action
  8. Workshop
    Monitoring Constraints for Robotic Tutors in Nurse Education: A Motion Planning Perspective
    Qingxi Meng*Carlos Quintero-Peña*Zachary Kingston , Nicole M. Fontenot , Shannan K. Hamlin , and 2 more authors
    In IEEE ICRA 2024 Workshop—Workshop on Nursing Robotics

2023

  1. Robots as AI Double Agents: Privacy in Motion Planning
    In IEEE/RSJ International Conference on Intelligent Robots and Systems
  2. Solving Rearrangement Puzzles using Path Defragmentation in Factored State Spaces
    S. Bora Bayraktar , Andreas OrtheyZachary KingstonMarc Toussaint , and Lydia E. Kavraki
    IEEE Robotics and Automation Letters
  3. Object Reconfiguration with Simulation-Derived Feasible Actions
    Yiyuan Lee , Wil ThomasonZachary Kingston , and Lydia E. Kavraki
    In IEEE International Conference on Robotics and Automation
  4. Optimal Grasps and Placements for Task and Motion Planning in Clutter
    In IEEE International Conference on Robotics and Automation
  5. Scaling Multimodal Planning: Using Experience and Informing Discrete Search
    IEEE Transactions on Robotics

2022

  1. Robowflex: Robot Motion Planning with MoveIt Made Easy
    In IEEE/RSJ International Conference on Intelligent Robots and Systems

2021

  1. MotionBenchMaker: A Tool to Generate and Benchmark Motion Planning Datasets
    IEEE Robotics and Automation Letters
  2. Using Experience to Improve Constrained Planning on Foliations for Multi-Modal Problems
    In IEEE/RSJ International Conference on Intelligent Robots and Systems
  3. HyperPlan: A Framework for Motion Planning Algorithm Selection and Parameter Optimization
    In IEEE/RSJ International Conference on Intelligent Robots and Systems
  4. Learning Sampling Distributions Using Local 3D Workspace Decompositions for Motion Planning in High Dimensions
    In IEEE International Conference on Robotics and Automation
  5. Finite Horizon Synthesis for Probabilistic Manipulation Domains
    In IEEE International Conference on Robotics and Automation

2020

  1. Planning Under Manifold Constraints, Encyclopedia of Robotics
  2. Informing Multi-Modal Planning with Synergistic Discrete Leads
    In IEEE International Conference on Robotics and Automation
  3. Decoupling Constraints from Sampling-Based Planners
    In Robotics Research

2019

  1. Exploring Implicit Spaces for Constrained Sampling-Based Planning
    The International Journal of Robotics Research

2018

  1. Distributed Object Characterization with Local Sensing by a Multi-Robot System
    Golnaz Habibi , Sándor P. Fekete ,  Zachary Kingston , and James McLurkin
    In Distributed Autonomous Robotic Systems
  2. An Incremental Constraint-Based Framework for Task and Motion Planning
    The International Journal of Robotics Research, Special Issue on the 2016 Robotics: Science and Systems Conference
  3. Sampling-Based Methods for Motion Planning with Constraints
    Annual Review of Control, Robotics, and Autonomous Systems

2017

  1. Robonaut 2 and You: Specifying and Executing Complex Operations
    William Baker ,  Zachary KingstonMark Moll , Julia Badger , and Lydia E. Kavraki
    In IEEE Workshop on Advanced Robotics and its Social Impacts

2016

  1. Incremental Task and Motion Planning: A Constraint-Based Approach
    In Robotics: Science and Systems

2015

  1. Kinematically Constrained Workspace Control via Linear Optimization
    In IEEE-RAS International Conference on Humanoid Robots
  2. Pipelined Consensus for Global State Estimation in Multi-Agent Systems
    Golnaz HabibiZachary Kingston , Zijian Wang , Mac Schwager , and James McLurkin
    In Proceedings of the 2015 International Conference on Autonomous Agents and Multiagent Systems
  3. Distributed Centroid Estimation and Motion Controllers for Collective Transport by Multi-Robot Systems
    Golnaz HabibiZachary Kingston , William Xie , Mathew Jellins , and James McLurkin
    In IEEE International Conference on Robotics and Automation