Learn from Incomplete Tactile Data: Tactile Representation Learning with Masked Autoencoders

Understand

The missing signal caused by the objects being occluded or an unstable sensor is a common challenge during data collection.

• Such missing signals will adversely affect the results obtained from the data, and this issue is observed more frequently in robotic tactile perception.
• In tactile perception, due to the limited working space and the dynamic environment, the contact between the tactile sensor and the object is frequently insufficient and unstable, which causes the partial loss of signals, thus leading to incomplete tactile data.
• The tactile data will therefore contain fewer tactile cues with low information density.