We present a distributed control strategy for the aggregation of multiple modular robots into one connected structure optimized for use with 3D modular pivoting cube robots such as the 3D M-Blocks [1]. We use the intensity from a light source as input to a decentralized control algorithm that drives the robots together. We describe the algorithm, give provable guarantees on convergence, and discuss experiments carried out in simulation and with a hardware platform of ten 3D M-Blocks modules. In this paper we contribute provably correct algorithms for the aggregation of generic modular robots; we show how these algorithms can be applied on real hardware by evaluating them on the 3D M-Blocks platform.

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.

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.

We present our digital fabrication technique for manufacturing active objects in 2D from a collection of smart particles. Given a passive model of the object to be formed, we envision submerging this original in a vat of smart particles, executing the new shape duplication algorithm described in this paper, and then brushing aside any extra modules to reveal both the original object and an exact copy, side-by-side. Extensions to the duplication algorithm can be used to create a magnified version of the original or multiple copies of the model object. Our novel duplication algorithm uses a distributed approach to identify the geometric specification of the object being duplicated and then forms the duplicate from spare modules in the vicinity of the original. This paper details the duplication algorithm and the features that make it robust to (1) an imperfect packing of the modules around the original object; (2) missing communication links between neighboring modules; and (3) missing modules in the vicinity of the duplicate object(s). We show that the algorithm requires O(1) storage space per module and that the algorithm exchanges O(n) messages per module. Finally, we present experimental results from 60 hardware trials and 150 simulations. These experiments demonstrate the algorithm working correctly and reliably despite broken communication links and missing modules.

This paper describes several novel algorithms for shape formation by subtraction in programmable matter systems. These algorithms allow the simultaneous formation of multiple different shapes from a single block of host material. The resulting shapes are allowed to intertwine in arbitrarily complex ways. We also present a proof that the algorithms operate correctly to form the desired shapes. Finally, we show experimental results from close to 100 trials using both the Robot Pebbles hardware and a unique software simulator. Multiple trials of several different experiments demonstrate the algorithms operating correctly.

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.

We describe the design, implementation, and experimentation with a collection of robots that, starting from an amorphous arrangement, can be assembled into arbitrary shapes and then commanded to self-disassemble in an organized manner. 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. Two cooperating 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. We report on the hardware design and experiments from hundreds of trials.