Created: September 19, 2022

Tags: 6D Pose, Point Cloud, Tactile, Gelsight

Link: https://www.researchgate.net/profile/Snehal_Dikhale/publication/357842538_VisuoTactile_6D_Pose_Estimation_of_an_In-Hand_Object_Using_Vision_and_Tactile_Sensor_Data/links/6297b925416ec50bdb022987/VisuoTactile-6D-Pose-Estimation-of-an-In-Hand-Object-Using-Vision-and-Tactile-Sensor-Data.pdf

Status: Reading

What?

Existing 6D pose estimation methods use vision data. In-hand 6D object pose estimation is challenging because of heavy occlusion produced by the robot’s grippers. Tactile sensors at fingertips can be used to complement the vision data.

Why?

How?

Pipeline:

• Use point clouds to represent object surfaces that are in contact with tactile sensor.
• Use a network architecture based on pixel-wise dense fusion to fuse vision and tactile data. The fusion method is proposed by Wang et al.