Jason Campbell

Programmable matter

In the past 50 years, computers have shrunk from room-size mainframes to lightweight handhelds. This fantastic miniaturization is primarily the result of high-volume nanoscale manufacturing. While this technology has predominantly been applied to logic and memory, its now being used to create advanced microelectromechanical systems using both top-down and bottom-up processes. One possible outcome of continued progress in high-volume nanoscale assembly is the ability to inexpensively produce millimeter-scale units that integrate computing, sensing, actuation, and locomotion mechanisms. A collection of such units can be viewed as a form of programmable matter.

A Robust Visual Odometry and Precipice Detection System Using Consumer-grade Monocular Vision

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.

IrisNet: an internet-scale architecture for multimedia sensors

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.

Techniques for evaluating optical flow for visual odometry in extreme terrain

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.

A Language for Large Ensembles of Independently Executing Nodes

We address how to write programs for distributed computing systems in which the network topology can change dynamically. Examples of such systems, which we call ensembles , include programmable sensor networks (where the network topology can change due to failures in the nodes or links) and modular robotics systems (whose physical configuration can be rearranged under program control). We extend Meld [1], a logic programming language that allows an ensemble to be viewed as a single computing system. In addition to proving some key properties of the language, we have also implemented a complete compiler for Meld. It generates code for TinyOS [14] and for a Claytronics simulator [12]. We have successfully written correct, efficient, and complex programs for ensembles containing over one million nodes.

Programming modular robots with locally distributed predicates

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.

Generalizing metamodules to simplify planning in modular robotic systems

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.

Electrostatic latching for inter-module adhesion, power transfer, and communication in modular robots

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/cm2 of latch area.

Distributed Localization of Modular Robot Ensembles

Internal localization, the problem of estimating relative pose for each module of a modular robot, is a prerequisite for many shape control, locomotion, and actuation algorithms. In this paper, we propose a robust hierarchical approach that uses normalized cut to identify dense sub-regions with small mutual localization error, then progressively merges those sub-regions to localize the entire ensemble. Our method works well in both two and three dimensions, and requires neither exact measurements nor rigid inter-module connectors. Most of the computations in our method can be distributed effectively. The result is a robust algorithm that scales to large ensembles. We evaluate our algorithm in two- and three-dimensional simulations of scenarios with up to 10,000 modules.

The robot is the tether: active, adaptive power routing modular robots with unary inter-robot connectors

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.