MoveIt! [ROS Topics]

By Sachin Chitta, Ioan Alexandru Sucan, Steve B. Cousins. IEEE Robotics Autom. Mag., 2012

452 citations recorded by the source corpus.

Subfields: Biophysics, Computational Mechanics, Economics and Econometrics

View Paper: https://www.semanticscholar.org/paper/2fdaa008a1fb20a8dee35e9d8cab2a7ead35c264

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Citations in the corpus

Finding Locally Optimal, Collision-Free Trajectories with Sequential Convex Optimization (2013, methodology): “We are also working on a MoveIt plugin [5] so our software can be used along with ROS tools.”
Learning to Manipulate Deformable Objects without Demonstrations (2019, methodology): “Since apick and aplace are both defined as points on the image, we can easily command the robot to perform pick-place operations on the deformable object placed on the green table by planning with Moveit! [5].”
Yale-CMU-Berkeley dataset for robotic manipulation research (2017, methodology): “…Operating System (ROS; Quigley et al., 2009) node is available at YCB-Benchmarks (2016a) to manage the data and generate Unified Robot Description Files (URDFs) of the mesh models for easy integration to software platforms such as Gazebo (Koenig and Howard, 2004) and MoveIt (Chitta et al., 2012).”
Survey of Robot 3D Path Planning Algorithms (2016, background): “RRT has the advantage of handling multi-DOF problems; thus it is widely used for PR2 and other robots [94].”
PyRobot: An Open-source Robotics Framework for Research and Benchmarking (2019, background): “[20], OMPL [59] which provide hardware-agnostic core functionalities that can be compiled for each spe-ciﬁc robot.”
SAPIEN: A SimulAted Part-Based Interactive ENvironment (2020, background): “Thus, at the highest level, we provide motion planning support based on the popular MoveIt framework [9], which can generate motion plans that effectively move the robot around without collision.”
Whole-body motion planning for manipulation of articulated objects (2013, methodology): “Our planner is implemented in the MoveIt! framework in ROS [8] and uses FCL [23] for collision checks.”
6-DOF Grasping for Target-driven Object Manipulation in Clutter (2019, methodology): “It is worth noting that the surface-normal based sampler performed well for simpler shapes like boxes but failed to generate grasps for more complex geometry with rim, handles, etc. CollisionNet vs Voxel-Based Collision Checking: We compared the effectiveness of CollisionNet with a voxel-based heuri”
What Should I Do Now? Marrying Reinforcement Learning and Symbolic Planning (2019, background): “Conversely, many robotics systems still favor planning and search techniques such as RRTs and A* over the reactive Deep RL counterparts [9, 29].”
Motion planning with sequential convex optimization and convex collision checking (2014, methodology): “We are also working on a MoveIt plugin [4] so our software can be used along with ROS tools.”