Capturing robot workspace structure: representing robot capabilities
By Franziska Zacharias, C. Borst, G. Hirzinger. 2007 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2007
305 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Control and Systems Engineering
View Paper: https://www.semanticscholar.org/paper/53271ecd9d1adde34ef6b674a771b9b90b07bebb
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
In Control and Systems Engineering
- Lorenzo Jamone
- Giulio Sandini
- Lorenzo Natale
- Rachid Alami
- G. Hirzinger
- Amit Kumar Pandey
- Alin Olimpiu Albu-Schäffer
- Sami Haddadin
Citations in the corpus
- Making planned paths look more human-like in humanoid robot manipulation planning (2011, methodology): “The spheres are colored with respect to their reachability index D [13] which is the percentage of points on the sphere that are reachable.”
- Mightability maps: A perceptual level decisional framework for co-operative and competitive human-robot interaction (2010, background): “In [5], the kinematic reachability and directional structure for the robot arm has been generated.”
- Autonomous online generation of a motor representation of the workspace for intelligent whole-body reaching (2014, methodology): “A richer description of the robot workspace is provided in [26], where reachable points in space are ranked by their reachability, a measure indicating the number of possible approaching directions for the arm (note that the definition of reachability in [26] is different from the one we propose in ”