Annan Mozeika

Universal robotic gripper based on the jamming of granular material

Gripping and holding of objects are key tasks for robotic manipulators. The development of universal grippers able to pick up unfamiliar objects of widely varying shape and surface properties remains, however, challenging. Most current designs are based on the multifingered hand, but this approach introduces hardware and software complexities. These include large numbers of controllable joints, the need for force sensing if objects are to be handled securely without crushing them, and the computational overhead to decide how much stress each finger should apply and where. Here we demonstrate a completely different approach to a universal gripper. Individual fingers are replaced by a single mass of granular material that, when pressed onto a target object, flows around it and conforms to its shape. Upon application of a vacuum the granular material contracts and hardens quickly to pinch and hold the object without requiring sensory feedback. We find that volume changes of less than 0.5% suffice to grip objects reliably and hold them with forces exceeding many times their weight. We show that the operating principle is the ability of granular materials to transition between an unjammed, deformable state and a jammed state with solid-like rigidity. We delineate three separate mechanisms, friction, suction, and interlocking, that contribute to the gripping force. Using a simple model we relate each of them to the mechanical strength of the jammed state. This advance opens up new possibilities for the design of simple, yet highly adaptive systems that excel at fast gripping of complex objects.

JSEL: Jamming Skin Enabled Locomotion

A soft, mobile, morphing robot is a desirable platform for traversing rough terrain and navigating into small holes. In this work, a new paradigm in soft robots is presented that utilizes jamming of a granular medium. The concept of activators (as opposed to actuators) is presented to jam and unjam cells that then modulate the direction and amount of work done by a single central actuator. A prototype jamming soft robot utilizing JSEL (Jamming Skin Enabled Locomotion) with external power and control is discussed and both morphing results and mobility (rolling) results are presented. Future directions for the design of a soft, hole traversing robot are discussed, as is the role and promises of jamming as an enabling technology for soft robotics.

The first steps of a robot based on jamming skin enabled locomotion

A soft, controllably morphable mobile robot is an ideal platform for traversing complex terrain and navigating small holes. iRobot Corporation and the University of Chicago have made use of a phenomenon known as particle jamming to create such a robot. The robot presented in this work uses jamming skin cells to enable controlled morphing and locomotion.

Using Morphogenetic Models to Develop Spatial Structures

A common problem in spatial computing is how to arrange the structure of a spatial computer into a geometric form adapted for its current environment and needs. In natural biological organisms, the processes of morphogenesis adapt structure to environment remarkably well on both an individual and evolutionary time scale. However, no clear framework has been developed for exploiting morphogenetic principles in the creation of engineered systems. In this paper, we present preliminary work toward such a framework, developed against the example of a robot similar to the iRobot LANdroid. We first show how developmental programs might act as a reference architecture for engineered designs, facilitating variation. We then present a candidate basis set of geometric operations for encoding adaptable developmental programs, demonstrate how they can be applied to develop a robot body plan, and discuss progress toward implementation.

A manifold operator representation for adaptive design

Many natural organisms exhibit canalization: small genetic changes are accommodated by adaptation in other systems that interact with them. Engineered systems, however, are typically quite brittle, making design automation extremely difficult. We propose to address this problem with a generative representation of design based on manifold operators. The operator set we propose combines the intuitive simplicity of top-down rewrite rules with the flexibility and distortion tolerance of bottom-up GRN-based models. An embryogeny specified using this representation thus places constraints on a developing design, rather than specifying a fixed body plan, allowing canalization processes to modulate the design as it continues to develop. We demonstrate our ideas in the domain of electromechanical design and validate them with simulations at different levels of abstraction.

Managing Design Change with Functional Blueprints

Long-lived complex electromechanical systems, such as vehicles or industrial machinery, often need to be adapted for new uses or new environments. Adapting the design for such a system is frequently complicated by the fact that they are often tightly integrated, such that any change will have consequences throughout the design, and must take many different aspects of the system into consideration. Functional blueprints simplify adaptation by incorporating the reasons for design decisions and their consequences directly into the specification of a system. This allows a human designer to be supported by automated reasoning that can identify potential conflicts, suggest design fixes, and propagate changes implicit in the choices of the designer. This chapter presents the functional blueprints approach in detail, including both review of prior work and new results.