Grippers and Sensors for Soft Robots

Our lives in modern society are easier in many ways due to the ongoing revolution of robotics. Robots perform endless tasks in assembly lines and in factories making our work lighter and decreasing the need for human labour. To repeat these precise and heavy tasks millions of times, the robots—including actuators, sensors, and control and power units—are made of hard and tough materials. The hard robots are needed in factories but at the same time the hardness of the robots limits the safety and the comfort while working near humans. The research in soft materials has opened new possibilities in robotics, creating a new field called soft robotics. By shifting from the hard robot materials to soft ones, the robots can be 1) made safer: they cause less damage, even in collision; 2) made to conform to objects; and 3) made to feel comfortable against the skin.

Many of the manufacturing methods of soft robots have been adapted from the field of microfluidics. Silicone casting has been widely used to fabricate chips with detailed small structures. The method is efficient for replicating small features. However, complex structures, such as overhangs and buried channels, are particularly difficult to fabricate since the elastomer piece must be removed from the mould. In soft robotics, these kinds of structures are often desired for creating moving actuators and grippers. An efficient and fast way to fabricate fully three-dimensional soft structures is still needed.

Grippers made of soft materials can conform to objects, which can enable the picking of fragile objects without damaging them. However, it can limit the holding forces while carrying the object. During the object transport it can be beneficial if the gripper material is stiff or even rigid. Materials and mechanisms with controllable stiffness could be used to achieve this effect.

In addition to the soft body of the robot, the sensors need to also be stretchable and soft. One of the most important types of sensors used in soft robots is the strain sensor which in different configurations can measure exteroceptive and proprioceptive information. Many methods for fabricating soft strain sensors have been proposed, such as liquid metals and ionic conductors. However, many of these methods involve multiple fabrication steps or materials which are difficult to handle, so they are not suitable for mass manufacturing. Additionally, these sensors are usually electrical, unlike soft actuators which are often pneumatic. Using pneumatics also for the sensing would simplify the overall structure of the robot.

This thesis explores different methods of designing and fabricating soft robots and sensors for them. First, we studied whether sacrificial 3D printing was a suitable method of fabricating soft devices moulds with overhanging structures. We were able to demonstrate that the proposed method is straightforward and can be used to fabricate buried channels in soft silicone elastomer structures. Second, we developed soft robotic grippers. We fabricated two different 3D printed suction-based grippers: a pneumatic one and a magnetically switchable hydraulic one. 3D printing was found to be a suitable method for soft gripper fabrication. We also found that the grippers outperformed commercial suction grippers with small, unevenly loaded and fragile objects. We propose using magnetorheological fluid, embedded inside a soft robotic gripper, to control the stiffness of the gripper. Last, the sensors were fabricated and integrated into soft robots. Two different approaches were proposed for strain and curvature sensing: screen-printed stretchable sensors and soft pneumatic strain sensors. We propose that screen-printing is a low-cost method suitable for mass manufacturing electric strain sensors, whereas soft pneumatic strain sensors are a step towards fully pneumatic soft robots.

To conclude, this dissertation describes new methods of fabricating soft robots and sensors for them, aiming at simpler ways to fabricate smarter soft robots with perception.