Dynamically-Stable Motion Planning for Humanoid Robots
By James J. Kuffner Jr., S. Kagami, K. Nishiwaki, Masayuki Inaba, Hirochika Inoue. Auton. Robots, 2002
322 citations recorded by the source corpus.
Subfields: Biomedical Engineering, Computer Vision and Pattern Recognition, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/c66bf1cb21a21fc90930f21bcb0eac231f255ca5
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
In Computer Vision and Pattern Recognition
- Sertac Karaman
- Emilio Frazzoli
- Maren Bennewitz
- Felix Burget
- Armin Hornung
- Markus Achtelik
- Jur van den Berg
- Dustin J. Webb
In Control and Systems Engineering
- Emilio Frazzoli
- Sertac Karaman
- Maren Bennewitz
- Armin Hornung
- Alberto Rodriguez
- Nikhil Chavan Dafle
- Vijay R. Kumar
- Siddhartha S. Srinivasa
Citations in the corpus
- Whole-body motion planning for manipulation of articulated objects (2013, methodology): “[12] were the first who applied probabilistic motion planning to generate wholebody motions for humanoids.”
- Incremental Sampling-based Algorithms for Optimal Motion Planning (2010, methodology): “Moreover, the RRT algorithm was demonstrated in major robotics events on various experimental robotic platforms [38]–[42].”
- Optimal kinodynamic motion planning using incremental sampling-based methods (2010, unknown): “Recently, the RRT algorithm and its variants were successfully demonstrated on different robotic platforms in major robotics events (see, e.g., [4], [15], [16]).”
- Sampling-based algorithms for optimal motion planning (2011, methodology): “Moreover, the RRT algorithm was demonstrated in major robotics events on various experimental robotic platforms (Kuffner et al. 2002; Bruce and Veloso 2003; Kuwata et al. 2009; Teller et al. 2010; Shkolnik et al. 2011).”