Browsing by Author "Lonsford, Jarrett"
Now showing 1 - 3 of 3
- Results Per Page
- Sort Options
Item Deploying Sensor Modules with Remotely Operated Underwater Robots for Marine Data Collection(2017-10-12) Lonsford, JarrettOcean Big Data (OBD) has become prominent in environmental monitoring, offshore exploration and military surveillance. Secure transfer of this data to the surface can be challenging. Magnetic induction (MI) and visible light communications (VLC) have relatively small ranges. Our approach uses a remotely operated vehicle (ROV) swarm to deploy, recharge and retrieve sensors.Item Parallel Self-Assembly of Polyominoes Under Uniform Control Inputs(IEEE Robotics and Automation Letters, 6/15/2017) Manzoor, Sheryl; Sheckman, Samuel; Lonsford, Jarrett; Kim, Hoyeon; Kim, Min Jun; Becker, Aaron T.We present fundamental progress on parallel self-assembly using large swarms of microscale particles in complex environments, controlled not by individual navigation, but by a uniform, global, external force with the same effect on each particle. Consider a 2-D grid world, in which all obstacles and particles are unit squares, and for each actuation, particles move maximally until they collide with an obstacle or another particle. We present algorithms that, given an arbitrary 2-D structure, design an obstacle layout. When actuated, this layout generates copies of the input 2-D structure. We analyze the movement and spatial complexity of the factory layouts. We present hardware results on both a macroscale, gravity-based system, and a microscale, magnetically actuated system.Item Particle Computation: Complexity, Algorithms, and Logic(Natural Computing, 12/8/2017) Becker, Aaron T.; Demaine, Erik D.; Fekete, Sándor P.; Lonsford, Jarrett; Morris-Wright, RoseWe investigate algorithmic control of a large swarm of mobile particles (such as robots, sensors, or building material) that move in a 2D workspace using a global input signal (such as gravity or a magnetic field). Upon activation of the field, each particle moves maximally in the same direction until forward progress is blocked by a stationary obstacle or another stationary particle. In an open workspace, this system model is of limited use because it has only two controllable degrees of freedom—all particles receive the same inputs and move uniformly. We show that adding a maze of obstacles to the environment can make the system drastically more complex but also more useful. We provide a wide range of results for a wide range of questions. These can be subdivided into external algorithmic problems, in which particle configurations serve as input for computations that are performed elsewhere, and internal logic problems, in which the particle configurations themselves are used for carrying out computations. For external algorithms, we give both negative and positive results. If we are given a set of stationary obstacles, we prove that it is NP-hard to decide whether a given initial configuration of unit-sized particles can be transformed into a desired target configuration. Moreover, we show that finding a control sequence of minimum length is PSPACE-complete. We also work on the inverse problem, providing constructive algorithms to design workspaces that efficiently implement arbitrary permutations between different configurations. For internal logic, we investigate how arbitrary computations can be implemented. We demonstrate how to encode dual-rail logic to build a universal logic gate that concurrently evaluates and, nand, nor, and or operations. Using many of these gates and appropriate interconnects, we can evaluate any logical expression. However, we establish that simulating the full range of complex interactions present in arbitrary digital circuits encounters a fundamental difficulty: a fan-out gate cannot be generated. We resolve this missing component with the help of 2 × 1 particles, which can create fan-out gates that produce multiple copies of the inputs. Using these gates we provide rules for replicating arbitrary digital circuits.