Catching Uneven Bananas

This is how it started.

Pay walled, but looks nice. Don’t be poor. This explains how to build motion dictionaries, kinematic chains, and other control structures to catch flying bananas. Learning Progressive Joint Propagation for Human Motion Prediction 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part VII.


This is how it’s going.

https://arxiv.org/abs/2103.08368

Neural Motion Prediction for In-flight Uneven Object Catching

Experimental results show that motion prediction with NAE and NAE-DF is superior to other methods and has a good generalization performance on unseen objects. We test our methods on a robot, performing velocity control in real world and respectively achieve 83.3% and 86.7% success rate on a ploy urethane banana and a gourd.

Hongxiang YuDashun GuoHuan YinAnzhe ChenKechun XuYue WangRong Xiong

RELATED

I don’t have time to read this, but maybe you do. Kalman filters are brilliant. https://ieeexplore.ieee.org/document/9281312 Human Motion Prediction Using Adaptable Recurrent Neural Networks and Inverse Kinematics.

Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Google photo

You are commenting using your Google account. Log Out /  Change )

Twitter picture

You are commenting using your Twitter account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s

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