Optimal Hand-Eye Calibration

By Klaus H. Strobl, G. Hirzinger. 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006

325 citations recorded by the source corpus.

Subfields: Control and Systems Engineering, Mechanical Engineering

View Paper: https://www.semanticscholar.org/paper/0646aaa662a8e0b2a0a2bbcad938d68cd45102f7

How researchers see this paper

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

In Control and Systems Engineering

1. Shirin Joshi
2. Ferat Sahin
3. Alessandro De Luca
4. Paolo Robuffo Giordano
5. Sulabh Kumra
6. Giuseppe Oriolo
7. Sami Haddadin
8. Alin Olimpiu Albu-Schäffer

In Mechanical Engineering

1. Alessandro De Luca
2. Shirin Joshi
3. Ferat Sahin
4. Sulabh Kumra

Citations in the corpus

• Rotation Averaging (2013, background): “Strobl and Hirzinger (2006) approached the problem by defining a metric on the group SE(3) and a corresponding error model for nonlinear optimization.”
• Antipodal Robotic Grasping using Generative Residual Convolutional Neural Network (2019, methodology): “The grasp pose is then converted from camera coordinates into robot coordinates using the transform calculated from hand-eye calibration [31].”
• Feature Depth Observation for Image-based Visual Servoing: Theory and Experiments (2008, background): “While typically both the camera hand–eye and intrinsic parameters are unknown but constant, and therefore they can be accurately estimated off-line once and for all (Strobl and Hirzinger 2006), vector t is made of unmeasurable timevarying quantities which need to be approximated in real implementati”