374 citations · 944 across the 24 of their papers we have counts for
3 papers · 1 filter
More Than a Feeling: Learning to Grasp and Regrasp using Vision and Touch
Roberto Calandra, Andrew Owens, Dinesh Jayaraman +5
For humans, the process of grasping an object relies heavily on rich tactile feedback. Most recent robotic grasping work, however, has been based only on visual input, and thus can…
The Feeling of Success: Does Touch Sensing Help Predict Grasp Outcomes?
Roberto Calandra, Andrew Owens, Manu Upadhyaya +4
A successful grasp requires careful balancing of the contact forces. Deducing whether a particular grasp will be successful from indirect measurements, such as vision, is therefore…
Shape-independent Hardness Estimation Using Deep Learning and a GelSight Tactile Sensor
Wenzhen Yuan, Chenzhuo Zhu, Andrew Owens +2
Hardness is among the most important attributes of an object that humans learn about through touch. However, approaches for robots to estimate hardness are limited, due to the lack…