computational robotics

from tasks to motions

The research in our group aims to increase the ability of robots to plan and act on their own or provide assistance in human-machine cooperative tasks in complex domains. Applications targeted in our research include mobile robotics, robot manipulation, medical robotics, and hybrid systems. We have also conducted research in large-scale parallelization of sampling-based motion planning and nearest-neighbors computations, approximate methods for dimensionality reduction and nearest neighbors, and characterization of molecular motion.
Follow the project pages for more information.
  • Unified Discrete and Continuous Planning

    Motion Planning with Linear Temporal Logic

    Motion Planning with AI Languages

  • Robotic Manipulation

    Object Recognition from Haptic Exploration and Tactile Appearance Information

  • Mobile Robotics

    Motion Planning with Differential Constraints

    Motion Planning in Configuration Spaces

  • Distributed Computing

    Sampling-based Roadmap of Trees

    Nearest-Neighbors Graph

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