In-hand manipulation is challenging for soft robotic hands, especially in the real world where robots encounter a variety of object sizes and shapes. As such, the role of the palm is crucial, providing stabilizing contact to objects during grasping and manipulation, and controlling the position of objects with respect to the fingertips. We demonstrate an actuated palm capable of enhancing the in-hand manipulation capabilities of a soft hand by better-utilizing limited finger dexterity. With a combination of physical and virtual experiments, we explore the effects of palm diameter and height on in-hand manipulation performance over a variety of object shapes and sizes, and three key manipulation primitive motions. The results of these experiments show that maintaining manipulation capabilities over a large range of object sizes requires the palm’s diameter to decrease as a function of its height to prevent interference between the fingers and palm. Based on these insights, we design an actuated palm mechanism that achieves the desired relationship between palm height and diameter using one actuated degree of freedom. Finally, we show that this adjustable palm enables the hand to manipulate a larger range of object sizes and aspect ratios, and its utility is demonstrated in a mid-air shelving in-hand manipulation task.

Engineers and scientists often rely on their intuition and experience when designing soft robotic systems. The development of performant controllers and motion plans for these systems commonly requires time-consuming iterations on hardware. We present the SoMo (Soft Motion) toolkit, a software framework that makes it easy to instantiate and control typical continuum manipulators in an accurate physics simulator. SoMo introduces a standardized and human-readable description format for continuum manipulators. It leverages this description format and the Bullet physics engine to enable fast and accurate simulations of soft and soft-rigid hybrid robots in environments with complex contact interactions. This allows users to vary design and control parameters across simulations with minimal effort. We compare the capabilities of SoMo to other physics simulators and highlight the benefits and accuracy of SoMo by demonstrating the agreement between simulation and real-world experiments on several examples; these include an in-hand manipulation task with continuum fingers, an automated exploration of how to design soft fingers for precision grasping, and a brief snake locomotion study. Overall, SoMo provides an accessible way for designers of soft robotic hardware and control systems to gain access to a simulation-accelerated workflow.