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Ioan A. Sucan
Researcher at Willow Garage
Publications - 31
Citations - 3529
Ioan A. Sucan is an academic researcher from Willow Garage. The author has contributed to research in topics: Motion planning & Mobile robot. The author has an hindex of 20, co-authored 31 publications receiving 2824 citations. Previous affiliations of Ioan A. Sucan include Rice University & International University, Cambodia.
Papers
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Journal ArticleDOI
The Open Motion Planning Library
TL;DR: The open motion planning library is a new library for sampling-based motion planning, which contains implementations of many state-of-the-art planning algorithms, and it can be conveniently interfaced with other software components.
Journal ArticleDOI
MoveIt! [ROS Topics]
TL;DR: MoveIt! will allow robots to build up a representation of their environment using data fused from three-dimensional (3-D) and other sensors, generate motion plans that effectively and safely move the robot around in the environment, and execute the motion plans while constantly monitoring the environment for changes.
Reducing the Barrier to Entry of Complex Robotic Software: a MoveIt! Case Study
TL;DR: The MoveIt! framework as discussed by the authors is an open-source tool for mobile manipulation in ROS that allows users to quickly get basic motion planning functionality with minimal initial setup, automate its configuration and optimization, and easily customize its components.
Book ChapterDOI
Towards Reliable Grasping and Manipulation in Household Environments
TL;DR: This work combines aspects such as scene interpretation from 3D range data, grasp planning, motion planning, and grasp failure identification and recovery using tactile sensors, aiming to address the uncertainty due to sensor and execution errors.
Book ChapterDOI
Kinodynamic Motion Planning by Interior-Exterior Cell Exploration
Ioan A. Sucan,Lydia E. Kavraki +1 more
TL;DR: Applications of motion planning have also expanded to fields such as graphics and computational biology, and the field that addresses planning for complex robots with kinematic and dynamic constraints is addressed.