Design Summary Draft 1


The article "This soft robotic gripper can screw in your light bulbs for you", (2017), a team of engineers at the University of California, San Diego, designed and built a soft robotic grip and its features. The soft robotic gripper can "pick up and manipulate objects without needing to see them and needing to be trained." It has three fingers made of pneumatic chambers which, have multiple degrees of freedom allowing manipulation of the held object. Each finger is covered with a "smart sensing skin made of silicone rubber" with embedded "sensors made of conducting carbon nanotubes". The sensing skin records and detects the nanotubes conductivity changes as the fingers bend. The data is then processed by the control board, which then creates a 3D model of the object the gripper is manipulating. As good as the soft robotic gripper is, there are similar products with more adaptable features like the FlexShaperGripper developed by Festo with collaboration with students from Oslo and Akershus University.

 The FlexShapeGripper, able to pick up objects with widest range of shapes. The gripper consists of a two cylinder which is filled with compressed air and water. The second chamber is attached with elastic silicone moulding, which acts like chameleon’s tongue. When the gripper approaches an object, the handling system guides the gripper across the object ensuring it is touching with the silicone cap. The air inside the pressurised chamber will be released through a small opening. The spring support inside the mechanism moves the piston upwards and the silicone cap pulls itself inwards. Then, the silicone cap wraps itself in a tightly form fit around the irregular object. All the mechanism inside the gripper is triggered by pressure. When holding an object, it does not require any extra energy. Thus, making the coordination easier between the handling system and gripper. The proportional valve helps to set the force and the deformation precisely to what is required. This allows several parts to be gripped at once in a single procedure.

Similarly, there are better gripper such as MultiChoiceGripper developed by Festo with collaboration with students with University of Linz. It was inspired by the human and modelled to the thumb. The grippers have a different type of grips, which allows the gripper to rotate its finger to grip in “parallel or centric” manner. The gripper is attached to the robotic arm with three compressed air tubes. The built-in cylinders are used to change the gripping manner and locking its gripping position by a mechanical locking system. Each finger is attached with pneumatic microcylinder which control the finger joint. With the addition of individual own drive system, it allows the finger to move individually using compressed air. The gripper has a T-shaped groove allows it to be adaptable and flexible which allows the finger to be replaceable. Also, requires no extra tools to replace the fingers of the gripper.

In conclusion, the soft robotic gripper would not be a better choice compared to another gripper like FlexShapeGripper and MultiChoiceGripper. It does not have any unique gripper finger features resembling chameleon’s tongue or resembling a human’s hand. The gripping mechanism of the FlexShapeGripper and MultichoiceGripper have a much more unique mechanism as the gripper are able to hold on different irregular object.

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Summary Draft 1

Summary Draft 1 The article "This soft robotic gripper can screw in your light bulbs for you" introduces how in 2017, a team of engineers at the University of California San Diego designed and built a soft robotic grip and its features. The soft robotic gripper can "pick up and manipulate objects without needing to see them and needing to be trained." It has three fingers made of pneumatic chambers which have many degrees of freedom allowing manipulation of the held object. Each of these three fingers is covered with a smart sensing skin made of silicone rubber with embedded sensors made of conducting carbon nanotubes. The sensing skin records and detects the nanotubes conductivity changes as the fingers bend. The data is then processed by the control board, which then creates a 3D model of the object the gripper is manipulating.
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