Parallel sampling-based motion planning with superlinear speedup

By Jeffrey Ichnowski, Ron Alterovitz. 2012

48 citations recorded by the source corpus.

Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Mechanical Engineering, Robotics & Control

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Biomedical Engineering

1. Ashutosh Saxena
2. Ashesh Jain

In Computer Vision and Pattern Recognition

1. Ashutosh Saxena
2. Thorsten Joachims
3. Ashesh Jain
4. Luc Van Gool
5. Kristen Grauman
6. Abhinav Kumar Gupta
7. Li Fei-Fei
8. Jitendra Malik

In Mechanical Engineering

1. Thorsten Joachims
2. Ashutosh Saxena

In Robotics & Control

1. Ashesh Jain
2. Thorsten Joachims
3. Brian Wojcik
4. Ashutosh Saxena
5. Andrew Y. Ng
6. Sergey Levine
7. Hema Swetha Koppula

Citations in the corpus

• Learning Trajectory Preferences for Manipulators via Iterative Improvement (2013, background): “ampling trajectories we refer interested readers to [11, 13]. 3When RRT becomes too slow, we switch to more efficient bidirectional-RRT. For even faster sampling one could use parallel samplers, e.g., [14]. It is important to note that sampling based methods (including ours) guarantees optimal soluti”