In this article, we formalize locally distributed predicates , a concept previously introduced to address specific challenges associated with modular robotics and distributed debugging. A locally distributed predicate (LDP) is a novel construction for representing and detecting distributed properties in sparse-topology systems. Our previous work on LDPs presented empirical validation; here we show a formal model for two variants of the LDP algorithm, LDP-Basic and LDP-Snapshot, and establish performance bounds for these variants. We prove that LDP-Basic can detect strong stable predicates, that LDP-Snapshot can detect all stable predicates, and discuss their applicability to various distributed programming domains and to spatial computing in general. LDP detection in bounded-degree networks is shown to be scale-free, making the approach particularly attractive for specific topologies, even though LDPs are less efficient than snapshot algorithms in general distributed systems.

LDP (Locally Distributed Predicates) is a distributed, high-level language for programming modular reconfigurable robot systems (MRRs). In this paper we present the implementation of two motion-planning algorithms in LDP, and analyze both their performance and ease of implementation. We present multiple variations of one planner, including a novel resource allocation algorithm. We then draw conclusions about both the utility of the motion-planning algorithms and the suitability of LDP to the problem space. Our experiments suggest that metamodule-based planning approaches have a cost in time and/or energy terms, but that the cost can be worth paying in exchange for the additional generality and separation-of-concerns offered by these techniques. The particular tradeoff for a given system will depend upon its goals and the details of the underlying modules.

This paper presents a novel biologically- inspired hierarchical approach to organizing and controlling modular robots. The purpose of our approach is to decompose the complexity of assembling and commanding a functional robot made of numerous simple modules (thousands to millions) by introducing a hierarchy of structure and control. The robots we describe incorporate anatomically-inspired parts such as muscles, bones and joints, and these parts in turn are assembled from modules. Each of those parts encapsulates one or more functions, e.g. a muscle can contract. Control of the robot can then be cast as a problem of controlling its anatomical parts rather than each discrete module. We show simulation results from experiments using gradient-based primitives to control parts of increasingly complex robots, including snake, crawler, cilia-surface, arm- joint-muscle and grasping robots. We conclude that this approach is promising for future many-modules systems, but is currently impractical on most existing platforms.

We present a high-level language for programming modular robotic systems, based on locally distributed predicates (LDP), which are distributed conditions that hold for a connected subensemble of the robotic system. An LDP program is a collection of LDPs with associated actions which are triggered on any subensemble that matches the predicate. The result is a reactive programming language which efficiently and concisely supports ensemble-level programming. We demonstrate the utility of LDP by implementing three common, but diverse, modular robotic tasks.

In this paper we develop a theory of metamodules and an associated distributed asynchronous planner which generalizes previous work on metamodules for lattice-based modular robotic systems. All extant modular robotic systems have some form of non-holonomic motion constraints. This has prompted many researchers to look to metamodules, i.e., groups of modules that act as a unit, as a way to reduce motion constraints and the complexity of planning. However, previous metamodule designs have been specific to a particular modular robot. By analyzing the constraints found in modular robotic systems we develop a holonomic metamodule which has two important properties: (1) it can be used as the basic unit of an efficient planner and (2) it can be instantiated by a wide variety of different underlying modular robots, e.g., modular robot arms, expanding cubes, hex-packed spheres, etc. Using a series of transformations we show that our practical metamodule system has a provably complete planner. Finally, our approach allows the task of shape transformation to be separated into a planning task and a resource allocation task. We implement our planner for two different metamodule systems and show that the time to completion scales linearly with the diameter of the ensemble.

Scaling down the module size of a self-reconfigurable robot will have a profound effect on the module's characteristics, e.g. strength to mass ratio. In this paper we explore how the characteristics of chains of modules, specifically locomotion velocity and best gait type, might change with the scale of those modules. The simulated experiments we report on here examine module sizes from (11 mum to 698 mum radius) and chain lengths from 3 to 30 modules. All gaits tested were based on central pattern generators optimized using a genetic algorithm and hill climbing. Our results show that scaling affects both the preferred type of gait as well as a chain's overall performance (average velocity). In summary, there is a tradeoff where larger scales face the challenge of overcoming gravity, while smaller sizes face the challenge of staying in contact with the ground and the friction it provides. We show that in between these two extremes lies a "best" module size for given environmental, physical, and engineering constraints

Tightly-coupled multi-agent systems such as modular robots frequently exhibit properties of interest that span multiple modules. These properties cannot easily be detected from any single module, though they might readily be detected by combining the knowledge of multiple modules. Testing for distributed conditions is especially important in debugging or verifying the correctness of software for modular robots. We have developed a technique we call distributed watchpoint triggers which can efficiently recognize such distributed conditions. Our watchpoint description language can handle a variety of temporal, spatial, and logical properties spanning multiple robots. This paper presents that language, describes our fully-distributed, online mechanism for detecting distributed conditions in a running system, and evaluates the performance of our implementation. We found that the performance of the system is highly dependent on the program being debugged, scales linearly with ensemble size, and is small enough to make the system practical in all but the worst case scenarios

Creatively misquoting Thomas Hobbes, the process of software debugging is nasty, brutish, and all too long. This holds all the more true in robotics, which frequently involves concurrency, extensive nondeterminisism, event-driven components, complex state machines, and difficult platform limitations. Inspired by the challenges we have encountered while attempting to debug software on simulated ensembles of tens of thousands of modular robots, we have developed a new debugging tool particularly suited to the characteristics of highly parallel, event- and state-driven robotics software. Our state capture and introspection system also provides data that may be used in higher-level debugging tools as well. We report on the design of this promising debugging system, and on our experiences with it so far.

A simple and robust inter-module latch is possibly the most important component of a modular robotic system. This paper describes a latch based on electric fields and capacitive coupling. Our design provides not only significant adhesion forces, but can also be used for inter-module power transmission and communication. The key insight presented in this paper, and the factor that enables electrostatic adhesion to be effective at the macroscale, is the use of electric field attraction to generate frictional shear forces rather than electric field attraction alone. A second important insight is that a specific degree of flexibility in the electrodes is essential to maximize their mutual coupling and the resulting forces - electrodes which are too flexible or too rigid will perform less well. To evaluate the effectiveness of our latch we incorporate it into a cubic module 28 cm on a side. The result is a latch which requires almost zero static power and yet can hold 0.6 N/cm2of latch area.

One of the primary impediments to building ensembles of modular robots is the complexity and number of mechanical mechanisms used to construct the individual modules. As part of the Claytronics project - which aims to build very large ensembles of modular robots - we investigate how to simplify each module by eliminating moving parts and reducing the number of mechanical mechanisms on each robot by using force-at-a-distance actuators. Additionally, we are also investigating the feasibility of using these unary actuators to improve docking performance, implement intermodule adhesion, power transfer, communication, and sensing. In this paper we describe our most recent results in the magnetic domain, including our first design sufficiently robust to operate reliably in groups greater than two modules. Our work should be seen as an extension of systems such as Fracta [9], and a contrasting line of inquiry to several other researchers' prior efforts that have used magnetic latching to attach modules to one another but relied upon a powered hinge [10] or telescoping mechanism [12] within each module to facilitate self-reconfiguration.

We describe a novel shape formation algorithm for ensembles of 2-dimensional lattice-arrayed modular robots, based on the manipulation of regularly shaped voids within the lattice ("holes"). The algorithm is massively parallel and fully distributed. Constructing a goal shape requires time proportional only to the complexity of the desired target geometry. Construction of the shape by the modules requires no global communication nor broadcast floods after distribution of the target shape. Results in simulation show 97.3% shape compliance in ensembles of approximately 60,000 modules, and we believe that the algorithm will generalize to 3D and scale to handle millions of modules

This paper presents a novel application of modular robotic technology. Many researchers expect manufacturing technology will allow robot modules to be built at smaller and smaller scales, but movement and actuation are increasingly difficult as dimensions shrink. We describe an application - a 3D fax machine - which exploits inter-module communication and computation without requiring self-reconfiguration. As a result, this application may be feasible sooner than applications which depend upon modules being able to move themselves. In our new approach to 3D faxing, a large number of submillimeter robot modules form an intelligent "clay" which can be reshaped via the external application of mechanical forces. This clay can act as a novel input device, using intermodule localization techniques to acquire the shape of a 3D object by casting. We describe software for such digital clay. We also describe how, when equipped with simple inter-module latches, such clay can be used as a 3D output device. Finally, we evaluate results from simulations which test how well our approach can replicate particular objects

This demonstration presents a novel mechanism for the electronic acquisition of shapes of arbitrary objects, and the the remote reproduction of these shapes: in essence a 3D fax machine. Our approach is based on Claytronics, a form of intelligent matter or "smart clay" composed of thousands of tiny particles, each of which is a small electronic device capable of sensing, computation, communication, and actuation. For our purposes, this Claytronic material is treated as a network of thousands to millions of communicating sensor nodes that must work cooperatively to determine the shape of an object. We demonstrate the highly scalable software we have designed to permit such intelligent "clay" be used as both the input and output stages of a 3D fax machine through physics-based simulations.

Robot photographers have appeared in a variety of novelty settings over the past few years and typically have exploited rudimentary image-content-based approaches to identifying potential photographic subjects. These approaches are primarily limited to human subjects and further progress along content-based lines is hamstrung by slow progress on the general computer vision problem. In this paper, we present a mobile robot system which solves the group-picture-framing problem without requiring content-based methods. The system finds photographic subjects based on measurements of motion parallax obtained via optical flow during robot movements. Our method requires only sufficient contrast to permit reasonably accurate sparse optical flow field estimation and is completely independent of any content-based image heuristics. The result is a working mobile robot system that can correctly photograph human and non-human subjects in a variety of posed-subject situations, and produce well-framed, cropped images for printing on standard-sized photo paper.

We describe a monocular robot vision system which accomplishes accurate 3-DOF dead-reckoning, closed loop motion control, and precipice and obstacle detection, all in dynamic environments, using a single, consumer-grade web cam and typical laptop computer hardware. Simultaneous translation and rotation are accurately measured, and the camera need not be placed at the robot’s center of rotation. The algorithm is straightforward to implement and robust to noisy measurements. The software is based on open source computer vision libraries and is itself open source. It has been tested in a wide variety of real-world environments and on several different mobile robot platforms.

This paper describes a novel approach to powering a radical type of microrobot. Our long-term aim is to enable the construction of ensembles of millions of coordinated near-spherical, submillimeter microrobots. Both the large number of potential simultaneous neighbors of each robot (12) and the difficulty of fine actuation at such small scales preclude the use of complex connectors previously developed in many modular robotics efforts. Instead, we propose to leverage multirobot cooperation to simplify the mechanics of modular robot docking. In our approach, the robots actively cooperate to route virtual power busses (both supply and ground) to all the robots in the ensemble using only unary (single conductor) electrical connectors between robots. A unary connector allows for larger tolerances in engagement angle, simplifies robot manufacture, speeds reconfiguration, and maximizes the proportion of the connector surface area useful for carrying current. The algorithms we present permit a robot ensemble to efficiently harvest and distribute power from sources discovered in the environment and/or carried by the ensemble. We evaluate these algorithms in a variety of simulated deployment conditions and report on the impact of hardware defects, limited on-board power storage, and the ensemble-environment interface.

Most current sensor network research explores the use of extremely simple sensors on small devices called motes and focuses on over-coming the resource constraints of these devices. In contrast, our research explores the challenges of multimedia sensors and is motivated by the fact that multimedia devices, such as cameras, are rapidly becoming inexpensive, yet their use in a sensor network presents a number of unique challenges. For example, the data rates involved with multimedia sensors are orders of magnitude greater than those for sensor motes and this data cannot easily be processed by traditional sensor network techniques that focus on scalar data. In addition, the richness of the data generated by multimedia sensors makes them useful for a wide variety of applications. This paper presents an overview of IRISNET, a sensor network architecture that enables the creation of a planetary-scale infrastructure of multimedia sensors that can be shared by a large number of applications. To ensure the efficient collection of sensor readings, IRISNET enables the application-specific processing of sensor feeds on the significant computation resources that are typically attached to multimedia sensors. IRISNET enables the storage of sensor readings close to their source by providing a convenient and extensible distributed XML database infrastructure. Finally, IRISNET provides a number of multimedia processing primitives that enable the effective processing of sensor feeds in-network and at-sensor.

We propose a demonstration of extremely scalable modular robotics algorithms developed as part of the Claytronics Project (http://www-2.cs.cmu.edu/~claytronics/), as well as a demonstration of proof-of-concept prototypes. Our effort envisions multi-million-module robot ensembles able to morph into three-dimensional scenes, eventually with sufficient fidelity so as to convince a human observer the scenes are real. Although this work is potentially revolutionary in the sense that it holds out the possibility of radically altering the relationship between computation, humans, and the physical world, many of the research questions involved are similar in flavor to more mainstream systems research, albeit larger in scale. For instance, as in sensor networks, each robot will incorporate sensing, computation, and communications components. However, unlike most sensor networks each robot will also include mechanisms for actuation and motion. Many of the key challenges in this project involve coordination and communication of sensing and actuation across such large ensembles of independent units.

Motion vision (visual odometry, the estimation of camera egomotion) is a well researched field, yet has seen relatively limited use despite strong evidence from biological systems that vision can be extremely valuable for navigation. The limited use of such vision techniques has been attributed to a lack of good algorithms and insufficient computer power, but both of those problems were resolved as long as a decade ago. A gap presently yawns between theory and practice, perhaps due to perceptions of robot vision as less reliable and more complex than other types of sensing. We present an experimental methodology for assessing the real world precision and reliability of visual odometry techniques in both normal and extreme terrain. This paper evaluates the performance of a mobile robot equipped with a simple vision system in common outdoor and indoor environments, including grass, pavement, ice, and carpet. Our results show that motion vision algorithms can be robust and effective, and suggest a number of directions for further development.