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Tomas Lozano-Perez

Tomas Lozano-Perez

D-Index & Metrics

Computer Science

D-Index
66
Citations
32512
World Ranking
2254
National Ranking
1124

Research.com Recognitions

  • 2021 - IEEE Robotics & Automation Award “For foundational contributions to robot motion planning and visionary leadership of the field.”
  • 2017 - ACM Fellow For contributions to robotics, and motion planning, geometric algorithms, and their applications

Overview

Tomas Lozano-Perez is affiliated with MIT in the United States and primarily works in the field of Computer Science. Their research spans multiple subfields, including Artificial Intelligence, Computer Vision and Pattern Recognition, Control and Systems Engineering, Computer Networks and Communications, and Aerospace Engineering.

Their scientific contributions focus on a range of topics such as AI-based Problem Solving and Planning, Robotic Path Planning Algorithms, Robot Manipulation and Learning, Reinforcement Learning in Robotics, Machine Learning and Algorithms, Multimodal Machine Learning Applications, and Robotics and Sensor-Based Localization.

Among the recent published papers authored or co-authored by Tomas Lozano-Perez are:

  • "PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning" (2020) published in Proceedings of the International Conference on Automated Planning and Scheduling
  • "Learning compositional models of robot skills for task and motion planning" (2021) published in The International Journal of Robotics Research
  • "Planning with Learned Object Importance in Large Problem Instances using Graph Neural Networks" (2021) published in Proceedings of the AAAI Conference on Artificial Intelligence
  • "Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances" (2022) published in 2022 International Conference on Robotics and Automation (ICRA)
  • "From Machine Learning to Robotics: Challenges and Opportunities for Embodied Intelligence" (2021) published on arXiv (Cornell University)

Frequent co-authors include Leslie Pack Kaelbling, Joshua B. Tenenbaum, Tom Silver, Rohan Chitnis, and Aidan Curtis.

The most common venues for Tomas Lozano-Perez's publications are:

  • arXiv (Cornell University)
  • Proceedings of the AAAI Conference on Artificial Intelligence
  • The International Journal of Robotics Research
  • 2022 International Conference on Robotics and Automation (ICRA)
  • 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

Tomas Lozano-Perez has received recognition in their field, including the IEEE Robotics & Automation Award in 2021 for contributions to robot motion planning and visionary leadership, as well as being named an ACM Fellow in 2017 for contributions to robotics, motion planning, geometric algorithms, and their applications.

Best Publications

  • Solving the multiple instance problem with axis-parallel rectangles

    Thomas G. Dietterich;Richard H. Lathrop;Tomás Lozano-Pérez

  • Spatial planning: a configuration space approach

    T. Lozano-Pérez

  • An algorithm for planning collision-free paths among polyhedral obstacles

    Tomás Lozano-Pérez;Michael A. Wesley

  • A Framework for Multiple-Instance Learning

    Oded Maron;Tomás Lozano-Pérez

  • Automatic synthesis of fine-motion strategies for robots

    Tomás Lozano-pérez;Matthew T. Mason;Russell H. Taylor

  • Automatic Planning of Manipulator Transfer Movements

    Tomas Lozano-Perez

  • A subdivision algorithm in configuration space for findpath with rotation

    R. A. Brooks;T. Lozano-Perez

  • Model-based recognition and localization from sparse range or tactile data

    W. Eric;L. Grimson;Tomas Lozano-Perez

  • A simple motion-planning algorithm for general robot manipulators

    T. Lozano-Perez

  • On multiple moving objects

    M. Erdmann;T. Lozano-Perez

  • Robot Motion: Planning and Control

    Michale Brady;John M. Hollerbach;Timothy L. Johnson;Matthew T. Mason

  • Localizing Overlapping Parts by Searching the Interpretation Tree

    W. Eric L. Grimson;Tomas Lozano-Perez

  • An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization

    W.E.L. Grimson;G.J. Ettinger;S.J. White;T. Lozano-Perez

  • Hierarchical task and motion planning in the now

    Leslie Pack Kaelbling;Tomas Lozano-Perez

  • Hierarchical Planning in the Now

    Leslie Pack Kaelbling;Tomás Lozano-Pérez

  • System and method of registration of three-dimensional data sets including anatomical body data

    W. Eric L. Grimson;Steven J. White;Gil J. Ettinger;William M. Wells

  • Robot programming

    T. Lozano-Perez

  • An automatic registration method for frameless stereotaxy, image guided surgery, and enhanced reality visualization

    Unknown

  • Integrated task and motion planning in belief space

    Leslie Pack Kaelbling;Tomás Lozano-Pérez

  • Belief space planning assuming maximum likelihood observations

    Robert Platt;Russell Louis Tedrake;Leslie P. Kaelbling;Tomas Lozano-Perez

  • From Skills to Symbols: Learning Symbolic Representations for Abstract High-Level Planning

    George Dimitri Konidaris;Leslie Pack Kaelbling;Tomás Lozano-Pérez

Frequent Co-Authors

Ron Kikinis
Ron Kikinis Brigham and Women's Hospital
George Konidaris
George Konidaris Brown University
Wee Sun Lee
Wee Sun Lee National University of Singapore
David Hsu
David Hsu National University of Singapore

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