Grippers with a sense of touch
Ras Labs has combined material science innovation with data science and precision engineering to provide a state-of-the-art tactile sensor for robotic grippers.
Ras Labs' Tactile Fingertips and Tactile Control Wrist™ combine to form a powerful closed-loop manipulator of fragile and delicate objects with ease and precision.
In addition to electric grippers, our Tactile Fingertips and Tactile Pneumatic Controller™ also bring closed-loop manipulation to pneumatic robotics and automation.
The Tactile Pneumatic Controller, pictured right, connects to the Tactile Fingertips as well as an air supply to adjust grip strength on the fly.
Tactile pneumatic controller™
The Tactile Pneumatic Controller serves a similar purpose to the Tactile Control Wrist, but applies communications and actuation to pneumatics.
Pressurized air is controllably delivered to gently apply force and adjust for any slippage. Grip information and options are displayed through our user interface.
Features and benefits
accuracy
Our Fingertip sensor ranges from 0.05 N to 25 N sensitivity with 1 mm resolution in position. We can control a robotic gripper immediately in order to provide for an exceptionally gentle grasp of delicate objects.
Brittle objects like glassware and even an eggshell (on left) can be gripped, lifted, and placed without damage.
sensitivity
The sensitivity of our sensor is incredible. We can detect a very light touch (0.05 N force), and realized each sensor is capable of detecting heart beat pulses — including components of the pulse — at pulse points.
On the right, the Tactile Fingertips are shown picking up a single piece of paper by the edges without damage.
human-like control
Human touch is around 0.1 N force sensitivity. Ras Labs is looking to give traditional grippers the ability to pick up fragile objects with an uncannily human-like grasp in order to handle objects without damage from crushing or slippage.
On the left, the Tactile Fingertips are shown adjusting to a detected increase in force. The system grips harder in order to maintain good grasp.
data visualization
The quality of a good grasp comes from the integration of force and position. Our Tactile Control Wrist visualizes the Tactile Fingertip data to calibrate grip strength and speed.
machine learning
Our Tactile Fingertips use a variety of algorithms to acquire high precision data. Machine learning (ML) and artificial intelligence (AI) can also be utilized. ML identifies trends and patterns from collections of data. This provides a richness in the outputs of our sensor.
durability
Our patented soft and compliant yet durable material achieves better manipulation without damaging
an object's surface. Our Tactile Fingertips are robust (over 10 million cycles with full functionality), exceedingly sensitive, and have a wide pressure range.
We use custom workpieces to fatigue our Tactile Fingertips, including cycle testing in shear, shown on the right.