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Traditional parallel-jaw grippers are insufficient for delicate object manipulation due to their stiffness and lack of dexterity. Other dexterous robotic hands often have bulky fingers, rely on complex time-varying cable drives, or are prohibitively expensive. In this paper, we introduce a novel low-cost compliant gripper with two centimeter-scaled 3-DOF delta robots using off-the-shelf linear actuators and 3D-printed soft materials. To model the kinematics of delta robots with soft compliant links, which diverge from typical rigid links, we train neural networks using a perception system. Furthermore, we analyze the delta robot’s force profile by varying the starting position in its workspace and measuring the resulting force from a push action. Finally, we demonstrate the compliance and dexterity of our gripper through six dexterous manipulation tasks involving small and delicate objects. Thus, we present the groundwork for creating modular multi-fingered hands that can execute precise and low-inertia manipulations. 

Distributed manipulators - consisting of a set of actuators or robots working cooperatively to achieve a manipulation task - are robust and flexible tools for performing a range of planar manipulation skills. One novel example is the delta array, a distributed manipulator composed of a grid of delta robots, capable of performing dexterous manipulation tasks using strategies incorporating both dynamic and static contact. Hand-designing effective distributed control policies for such a manipulator can be complex and time consuming, given the high-dimensional action space and unfamiliar system dynamics. In this paper, we examine the principles guiding development and control of such a delta array for a planar translation task. We explore policy learning as a robust cooperative control approach, allowing for smooth manipulation of a range of objects, showing improved accuracy and efficiency over baseline human-designed policies. 

We design a compliant delta manipulator using 3D-printing and soft materials. Our design is different from the traditionally rigid delta robots as it is more accessible through low-cost 3D-printing, and can interact safely with its surroundings due to compliance. This work focuses on parallelogram links which are a key component of the delta robot design. We characterize these links over twelve dimensional parameters, such as beam and hinge thickness, and two material stiffness settings by displacing them, and observing the resulting forces and rotation angles. The parallelogram links are then integrated into a delta robot structure to test for delta mechanism behavior, which keeps the end-effector parallel to the base of the robot. We observed that using compliant hinges resulted in near-delta behavior, laying the groundwork for fabricating and utilizing 3D-printed compliant delta manipulators.