Researchers have developed a robotic hand with soft fingers capable of learning how to perform the pen spinning trick, the same one many of us have tried in school or work. This was accomplished through SWIFT, a system that learns to spin a pen through trial-and-error using only real-world data without requiring explicit prior knowledge of its physical attributes.
Utilizing self-labeled trials sampled from the real world, the system was able to discover the set of pen grasping and spinning primitive parameters that enables a soft hand to spin a pen robustly as well as reliably. After 130 sampled actions per object, SWIFT managed to achieve a 100% success rate across three objects with different weights and weight distributions.
- Build your own awesome, wearable mechanical hand that you operate with your own fingers.
- No motors, no batteries — just the power of air pressure, water, and your own hands!
- Hydraulic pistons enable the mechanical fingers to open and close and grip objects with enough force to lift them. Every finger joint can be adjusted...
The results highlight the potential for soft robotic end-effectors to perform dynamic tasks including rapid in-hand manipulation. We also demonstrate that SWIFT generalizes to spinning items with different shapes and weights such as a brush and a screwdriver which we spin with 10/10 and 5/10 success rates respectively,” said the researchers.
