Summary + Analysis Soft Robotic Gripper Draft 1

The article “This Soft Robotic Gripper Can Screw in Your Light Bulbs for You” (2017) introduces a new robotic gripper along with its design and functionalities. Developed by engineers at the University of California, San Diego, the three-finger gripper can lift and manipulate objects without visualization and training, enabling operations in dimmed and poor visibility. The article mentions each finger consists of three “pneumatic chambers”, providing the gripper various degrees of freedom. The movement of “pneumatic chambers” when air pressure is exerted allows the manipulation of objects. The fingers are overlaid with a “smart, sensing skin” manufactured with “silicone rubber”, implanted with sensors constructed of “carbon nanotubes”. As the fingers contract, the conductivity of the nanotubes varies, granting the skin recording and identification capabilities when the fingers are near an object. A control board houses the data generated by the sensors, gathering information to form a 3D model of the manipulated object. The article states future improvements including “machine learning” and “artificial intelligence”, as well as “3D printing” for increase durability of gripper’s fingers.

When compared to other related products on the market, the soft robotic gripper is lacking certain aspects and functionality. These include a lack of slip detector, lower number, and type of sensors compared to its competitors.

The soft robotic gripper is lacking a sensor that could detect slippage. When the gripper grabs an object, the object has a tendency to slip. An increase in grasping force to prevent slippage is necessary, however, the rise in force might damage fragile objects. Even though the soft robotic gripper has a “high coefficient of friction between the silicone elastomers.”, the engineering team at the University of California, San Diego, suggested taking slippages during grasping into consideration for their future work. In contrast to the “Intelligent Robotic Gripper with an Adaptive Grasp Technique (Johansson & Gull 2018), it has an “anti-slip” sensor that prevents slipping by raising grasping force without damaging delicate items.

Another limitation of the soft robotic gripper is its single tactile sensor, comprised of one stretch and strain sensor to detect contact and measure bending. Compared to the “Soft Robotic Fingers with Embedded Ionogel Sensors and Discrete Actuation Modes for Somatosensitive Manipulation (Truby, Katzschmann, Lewis & Rus 2019)”, which consist of four “soft resistive sensor”, 2 “curvature sensor”, and 2 “contact sensors”, embedded into each finger. These sensors work hand in hand, providing perception and awareness feedback when the gripper comes into contact with an object, resulting in complex manipulation and desirable feedback readings.