Contact detection and object size estimation using a modular soft gripper with embedded flex sensors

Soft-grippers can grasp delicate and deformable objects without bruise or damage as the gripper can adapt to the object’s shape. However, the contact forces are still hard to regulate due to missing contact feedback of such grippers. In this paper, a modular soft gripper design is presented utilizing interchangeable soft pneumatic actuators with embedded flex sensors as fingers of the gripper. The fingers can be assembled in different configurations using 3D printed connectors. The paper investigates the potential of utilizing the simple sensory feedback from the flex sensors to make additional meaningful inferences regarding the contact state and grasped object size. We study the effect of the grasped object size and contact type on the combined feedback from the embedded flex sensors of all fingers. Our results show that a simple linear relationship exists between the grasped object size and the final flex sensor reading at fixed input conditions, despite the variation in object weight and contact type. Additionally, by simply monitoring the time series response from the flex sensor, contact can be detected by comparing the response to the known free-bending response at the same input conditions. Furthermore, by utilizing the measured internal pressure supplied to the soft fingers, it is possible to distinguish between power and pinch grasps, as the nature of the contact affects the rate of change in the flex sensor readings against the internal pressure