This paper presents control and coordination algorithms for groups of vehicles. The focus is on autonomous vehicle networks performing distributed sensing tasks where each vehicle plays the role of a mobile tunable sensor. The paper proposes gradient descent algorithms for a class of utility functions which encode optimal coverage and sensing policies. The resulting closed-loop behavior is adaptive, distributed, asynchronous, and verifiably correct.

Coverage control for mobile sensing networks

Programmable matter is a material whose properties can be programmed to achieve specific shapes or stiffnesses upon command. This concept requires constituent elements to interact and rearrange intelligently in order to meet the goal. This paper considers achieving programmable sheets that can form themselves in different shapes autonomously by folding. Past approaches to creating transforming machines have been limited by the small feature sizes, the large number of components, and the associated complexity of communication among the units. We seek to mitigate these difficulties through the unique concept of self-folding origami with universal crease patterns. This approach exploits a single sheet composed of interconnected triangular sections. The sheet is able to fold into a set of predetermined shapes using embedded actuation. To implement this self-folding origami concept, we have developed a scalable end-to-end planning and fabrication process. Given a set of desired objects, the system computes an optimized design for a single sheet and multiple controllers to achieve each of the desired objects. The material, called programmable matter by folding, is an example of a system capable of achieving multiple shapes for multiple functions.

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Programmable matter by folding

In current robotics research there is a vast body of work on algorithms and control methods for groups of decentralized cooperating robots, called a swarm or collective. These algorithms are generally meant to control collectives of hundreds or even thousands of robots; however, for reasons of cost, time, or complexity, they are generally validated in simulation only, or on a group of a few tens of robots. To address this issue, this paper presents Kilobot, a low-cost robot designed to make testing collective algorithms on hundreds or thousands of robots accessible to robotics researchers. To enable the possibility of large Kilobot collectives where the number of robots is an order of magnitude larger than the largest that exist today, each robot is made with only $14 worth of parts and takes 5 minutes to assemble. Furthermore, the robot design allows a single user to easily operate a large Kilobot collective, such as programming, powering on, and charging all robots, which would be difficult or impossible to do with many existing robotic systems.

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Kilobot: A low cost scalable robot system for collective behaviors

From GuI to TuI Humans have evolved a heightened ability to sense and manipulate the physical world, yet the digital world takes little advantage of our capacity for hand-eye coordination. A tangible user interface (TUI) builds upon our dexterity by embodying digital information in physical space. Tangible design expands the affordances of physical objects so they can Graphical user interfaces (GUIs) let users see digital information only through a screen, as if looking into a pool of water, as depicted in Figure 1 on page 40. We interact with the forms below through remote controls, such as a mouse, a keyboard, or a touchscreen (Figure 1a). Now imagine an iceberg, a mass of ice that penetrates the surface of the water and provides a handle for the mass beneath. This metaphor describes tangible user interfaces: They act as physical manifestations of computation, allowing us to interact directly with the portion that is made tangible—the “tip of the iceberg” (Figure 1b). Radical Atoms takes a leap beyond tangible interfaces by assuming a hypothetical generation of materials that can change form and CoVer STorY

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Radical atoms: beyond tangible bits, toward transformable materials

Physical representations of data have existed for thousands of years. Yet it is now that advances in digital fabrication, actuated tangible interfaces, and shape-changing displays are spurring an emerging area of research that we call Data Physicalization. It aims to help people explore, understand, and communicate data using computer-supported physical data representations. We call these representations physicalizations, analogously to visualizations -- their purely visual counterpart. In this article, we go beyond the focused research questions addressed so far by delineating the research area, synthesizing its open challenges and laying out a research agenda.

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Opportunities and Challenges for Data Physicalization

In this paper, we describe a novel self-assembling, self-reconfiguring cubic robot that uses pivoting motions to change its intended geometry. Each individual module can pivot to move linearly on a substrate of stationary modules. The modules can use the same operation to perform convex and concave transitions to change planes. Each module can also move independently to traverse planar unstructured environments. The modules achieve these movements by quickly transferring angular momentum accumulated in a self-contained flywheel to the body of the robot. The system provides a simplified realization of the modular actions required by the sliding cube model using pivoting. We describe the principles, the unit-module hardware, and extensive experiments with a system of eight modules.

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M-blocks: Momentum-driven, magnetic modular robots

We describe the design, implementation and programming of a set of robots that, starting from an amorphous arrangement, can be assembled into arbitrary shapes and then commanded to self-disassemble in an organized manner to obtain a goal shape. We present custom hardware, distributed algorithms and experimental results from hundreds of trails which show the system successfully forming complex 3D shapes. Each of the 28 modules in the system is implemented as a 1.8-inch autonomous cube-shaped robot able to connect to and communicate with its immediate neighbors. Embedded microprocessors control each module's magnetic connection mechanisms and infrared communication interfaces. When assembled into a structure, the modules form a system that can be virtually sculpted using a computer interface and a distributed process. The group of modules collectively decides which elements are a part of the final shape and which are not using algorithms that minimize information transmission and storage. Finally, the modules not in the structure disengage their magnetic couplings and fall away under the influence of an external force: in this case, gravity.

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Miche: Modular Shape Formation by Self-Disassembly

This paper describes the design, fabrication, and experimental results of a programmable matter system capable of 2D shape formation through subtraction. The system is composed of autonomous 1cm modules which use custom-designed electropermanent magnets to bond, communicate, and share power with their neighbors. Given an initial block composed of many of these modules latched together in a regular crystalline structure, our system is able to form shapes by detaching the unnecessary modules. Many experiments show that the modules in our system are able to distribute data at 9600bps to their neighbors with a 98.5% success rate after four retries, and the connectors are able to support over 85 times the weight of a single module.

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Robot pebbles: One centimeter modules for programmable matter through self-disassembly

We have presented a detailed retrospective on modular robots and discussed connections between modular robots and programmable matter. This field has seen a great deal of creativity and innovation at the level of designing physical systems capable of matching shape to function and algorithms that achieve this capability. The success of these projects rests on the convergence of innovation in hardware design and materials for creating the basic building blocks, information distribution for programming the interaction between the blocks, and control. Most current systems have dimensions on the order of centimeters, yet pack computation, communication, sensing, and power transfer capabilities into their form factors. Additionally, these modules operate using distributed algorithms that use a modules ability to observe its current neighborhood and local rules to decide what to do next.

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Modular Robot Systems

This paper presents the mechanical design of a modular robot called the 3D M-Block, a 50mm cubic module capable of both independent and lattice-based locomotion. The first M-Blocks described in [1] could pivot about one axis of rotation only. In contrast, the 3D M-blocks can exert on demand both forward and backward torques about three orthogonal axes, for a total of six directions. The 3D M-Blocks transform these torques into pivoting motions which allow the new 3D M-Blocks to move more freely than their predecessors. Individual modules can employ pivoting motions to independently roll across a wide variety of surfaces as well as to join and move relative to other M-Blocks as part of a larger collective structure. The 3D M-Block maintains the same form factor and magnetic bonding system as the one-dimensional M-Blocks [1], but a new fabrication process supports more efficient and precise production. The 3D M-blocks provide a robust and capable modular self-reconfigurable robotic platform able to support swarm robot applications through individual module capabilities and self-reconfiguring robot applications using connected lattices of modules.

Kyle Gilpin

Papers

M-blocks: Momentum-driven, magnetic modular robots

Miche: Modular Shape Formation by Self-Disassembly

Robot pebbles: One centimeter modules for programmable matter through self-disassembly

Modular Robot Systems

3D M-Blocks: Self-reconfiguring robots capable of locomotion via pivoting in three dimensions