Manipulability Map

It often happens that you are interested to know in which area you robot has high manipulability and in which area it has low manipulability. There are several approaches for that. In this work, I implemented the Yoshikawa manipulability index. I discretized the joint space for each joint, then I compute the manipulability index and dump all data. Then I normalized the data and used OpenCV color map for better visualization.

In the following, you can see a pair of schunk LWA 4D manipulators and the corresponding manipulability map around the right arm. In this case, COLORMAP_HOT profile has been used for visualization, that mean yellow areas have high manipulability and brown areas have smaller manipulability.



0 0 votes
Article Rating
Notify of

This site uses Akismet to reduce spam. Learn how your comment data is processed.

Inline Feedbacks
View all comments
Would love your thoughts, please comment.x