This paper describes the development of a modular end-effector system (MEES) for autonomous robotic maintenance and repair tasks. The design consists of the following major components: Robot Side Mating Socket Module (RSMS), End-Effector Side Mating Socket Module (EEMS), the Modular Camera System (MCS), and Tool Holder/Changer unit. Multiple prototypes for each component have been manufactured, tested, and evaluated resulting in the final concept. Existing robotic tool-changer systems on the market were evaluated and features were built into the Modular End-Effector System to overcome the current limitations of those systems. A notable advantage to the MEES is that it is a robot agnostic system and simply uses an ISO standard bolt mounting pattern to physically attached to the robot of choice along with an ethernet connection. No external cables are required that could restrain the workspace of the robot manipulator. Additionally, it is compatible with customized wrist-mounted sensors and end-effectors without any modification of the actual robot circuitry. The MEES is demonstrated working with three different end-effectors and two different robots.

In this paper, we discuss the role of gripper compliance in successful grasping and manipulation of thin, flexible materials. We show, both conceptually and empirically, that each axis of compliance in a planar gripper provides unique benefits in this domain. Vertical compliance allows robust grasping of thin materials in the presence of large uncertainty in positioning. Lateral compliance increases opportunity to respond to unexpected snags by increasing the time window over which tensile forces are applied. Rotational compliance avoids damage to objects by decreasing the maximum tensile forces applied during snags. We explore these three benefits through empirical tests comparing a rigid gripper to a soft gripper, evaluating the level of vertical uncertainty each can handle for prehensile and non-prehensile manipulation, as well as the forces and displacements incurred during snags. The results show how a soft gripper's three-axis compliance provides a passive ability to prevent damage to delicate materials.

As robots begin to move from structured industrial environments to the real world, they must be equipped to not only safely interact with the environment, but also reason about how to leverage contact to perform tasks. In this work, we develop a modeling and motion planning framework for continuum robots that accounts for contact anywhere along the robot. We first present an analytical model for continuum manipulators under contact and discuss the ideal choice of generalized coordinates given properties of the manipulator and task specifications. We then demonstrate the utility of our model by developing a motion planning framework that can solve a diverse set of tasks. We apply our framework to end effector path planning for a soft arm in an obstacle-rich environment, and grasp planning for soft robotic grippers, where contact can happen anywhere on the arm or gripper. Finally, we verify the utility of our model and planning framework by planning a grasp with a desired contact force for a soft antipodal gripper and testing this grasp in a hardware demonstration. Overall, our model and planning approach further enhance soft and continuum robots where they already excel: utilizing contact with the world to achieve their goals with a gentle touch.

Robots are increasingly being called on to operate in settings and on tasks originally designed for humans, or where humans are also expected to work. Accordingly, the hardware and tools to be packaged, operated, or maintained are typically designed for use by humans, not robots. Robot autonomy in such cases can be expedited by a “robot factors” approach to the design of hardware, analogous to ergonomics for humans, taking typical current robot capabilities into account during the design process. In this paper, we present two case studies of redesigning mission-critical hardware in space habitats to facilitate autonomous robot operation. In both cases, hardware that previously required dexterous bi-manual manipulation is redesigned such that the entire maintenance task can be completed by a single robotic arm with a standard parallel jaw gripper. We demonstrate successful autonomous replacement of modules in the two hardware systems, and characterize how orientation and compliance of a grasp helps compensate for positioning errors. Based on our findings, we identify several key design strategies that underpin the robot factors approach to designing robot-friendly hardware, including consolidating compound actions into simpler mechanisms, constraining required motions to a single axis, and introducing mechanical compliance to mitigate the effects of pose uncertainties.

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.

The need for robotic hands capable of gentle in-hand manipulation is growing rapidly as robots enter the real world. In this work, we show that the arrangement of digits in a soft robotic hand has a strong effect on in-hand manipulation capabilities. Introducing task-based performance metrics which quantify the range of motion, repeatability, and accuracy of in-hand manipulation tasks, we investigate hand designs with finger arrangements ranging from axisymmetric-circular to anthropomorphic. Using an open-source soft robot simulator, the effect of object size and aspect ratio on the in-hand manipulation performance is studied for a variety of finger arrangements, and findings are validated using a physical hardware platform. We found that the ideal finger arrangement is task-dependent; anthropomorphic arrangements excel at lateral translations, and axisymmetric arrangements are best suited for rotations. The aspect ratio of the object also has a strong effect on in-hand manipulation, with anthropomorphic designs performing best on objects of high aspect ratio, and axisymmetric arrangements doing well on objects of low aspect ratio. These findings are further confirmed in a real-world task with delicate pastries, where gentle in-hand manipulation is critical. Overall, our results suggest that active control of digit arrangement is necessary for soft robotic hands to maximize in-hand manipulation capabilities with arbitrary objects.

In this work, we show that sensors based on soft, intentionally-lossy optical waveguides are well-suited for soft robotic grasping applications in the deep-sea. Each finger of a soft robotic hand is outfitted with a 2×1 array of optical sensing elements to enable proprioception and contact force sensing. Curvature sensing elements are integrated directly into the structure of a finger, while contact force sensors are fabricated as standalone units and attached afterward. Along with considerations for interfacing with deep-sea remotely operated vehicles (ROVs), models for the effect of bending on light loss and the effect of normal force on strain were used to inform sensor design decisions. Our sensors show sensitivity to curvature over a range of diameters from 8 mm to 76 mm, and sub-Newton force sensitivity. Additionally, sensors were characterized in simulated deep-sea environments at temperatures from -10°C to 50°C and hydrostatic pressures up to 4000 psi. The sensitivity of our curvature sensors is invariant to the temperatures and pressure ranges tested, though contact force sensors decreased in sensitivity as temperatures decreased. Finally, we successfully demonstrate that sensors onboard soft finger actuators can provide informative state feedback during grasping operations in air and water.