Nonparametric Bayesian Inference on Multivariate Exponential Families

We develop a model by choosing the maximum entropy distribution from the set of models satisfying certain smoothness and independence criteria; we show that inference on this model generalizes local kernel estimation to the context of Bayesian inference on stochastic processes. Our model enables Bayesian inference in contexts when standard techniques like Gaussian process inference are too expensive to apply. Exact inference on our model is possible for any likelihood function from the exponential family. Inference is then highly efficient, requiring only O (log N) time and O (N) space at run time. We demonstrate our algorithm on several problems and show quantifiable improvement in both speed and performance relative to models based on the Gaussian process.United States. Office of Naval Research (N00014-09-1-1052)United States. Office of Naval Research (N00014-10-1-0936

Autonomous gathering of livestock using a multi-functional sensor network platform

In this paper we develop algorithms and hardware for the autonomous gathering of cattle. We present a comparison of three different autonomous gathering algorithms that employ sound and/or electric stimuli to guide the cattle. We evaluate these algorithms in simulation by extending previous behavioral simulations for cattle. We implemented one of these algorithms and present data from experiments in which cattle were equipped with sensor nodes that allowed cueing with sound and electric stimuli. We discuss the minimum requirements for algorithms and hardware for autonomous gathering

Autonomous underwater data muling using wireless optical communication and agile autonomous underwater vehicle control

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2013.Cataloged from PDF version of thesis.Includes bibliographical references (p. 187-197).Underwater exploration and surveillance currently relies on subsea cables and tethers to relay data back to the user. The cause for this is that water heavily absorbs most electromagnetic signals, preventing effective radio communication over large distances, and that underwater communication with acoustic signals affords only bit rates on the the order of Kilobits per second. In this thesis we present a novel design and implementation for an underwater data muling system. This system allows for automatic collection of underwater datasets without the need to physically connect to or move the sensors by using mobile robots to travel to the sensors and download the data using wireless optical communication to bring it back to the base station. The system consists of two parts. The first part is a modular and adaptive robot for underwater locomotion in six degrees of freedom. We present a hardware design as well as control algorithms to allow for in-situ deployment without the need for manual configuration of the parameter space. To achieve this we designed a highly parameterizable controller and methods and algorithms for automatically estimating all parameters of this controller. The second part of the data mulling system is a novel high-bandwidth optical underwater communication device. This device allows for transfer of high-fidelity data, such as high-definition video and audio, images, and sensor logs. Finally we present algorithms to control the robots path in order to maximize data rates as it communicates with a sensor while using only the signal strength as a measurement. All components and algorithms of the system have been implemented and tested in the real world to demonstrate the validity of our claims.by Marek Wojciech Doniec.Ph.D

BiDirectional optical communication with AquaOptical II

This paper describes AquaOptical II, a bidirectional, high data-rate, long-range, underwater optical communication system. The system uses the software radio principle. Each AquaOptical II modem can be programmed to transmit user defined waveforms and record the received waveforms for detailed analysis. This allows for the use of many different modulation schemes. We describe the hardware and software architecture we developed for these goals. We demonstrate bidirectional communication between two AquaOptical II modems in a pool experiment. During the experiment AquaOptical II achieved a signal to noise ration of 5.1 over a transmission distance of 50 m at pulse widths of 1 μsec, 500 ns, and 250 ns. When using discrete pulse interval modulation (DPIM) this corresponds to a bit-rate of 0.57 Mbit/s, 1.14 Mbit/s, and 2.28 Mbit/s.Singapore. Defence Science & Technology AgencyUnited States. Multidisciplinary University Research Initiative. Antidote Projec

Complete SE[superscript 3] underwater robot control with arbitrary thruster configurations

e present a control algorithm for autonomous underwater robots with modular thruster configuration. The algorithm can handle arbitrary thruster configurations. It maintains the robot's desired attitude while solving for translational motion. The attitude can be arbitrarily chosen from the special orthogonal group SO[superscript 3] allowing the robot all possible orientations. The desired translational velocities can be chosen from R[superscript 3] allowing the robot to follow arbitrary trajectories underwater. If the robot is not fully holonomic then the controller chooses the closest possible solution using least squares and outputs the error vector. We verify the controller with experiments using our autonomous underwater robot AMOUR. We achieve roll errors of 1.0 degree (2.1 degrees standard deviation) and pitch errors of 1.5 degrees (1.8 degrees standard deviation). We also demonstrate experimentally that the controller can handle both nonholonomic and fully holonomic thruster configurations of the robot. In the later case we show how depth can be maintained while performing 360 degree rolls. Further, we demonstrate an input device that allows a user to control the robot's attitude while moving along a desired trajectory.Intel CorporationSingapore. Defence Science & Technology Agenc

Using optical communication for remote underwater robot operation

Underwater vehicles are typically operated using a tether or a slow acoustic link. We present an underwater optical communication system that enables a high-throughput and low-latency link to an underwater robot. The optical link allows the robot to operate in cluttered environments without the need for a tether. We demonstrate the performance of the system in a number of experiments which characterize the optical link and demonstrate remote control of the robot using a human input device.Singapore. Defence Science & Technology AgencyNational Science Foundation (U.S.).United States. Army Research Office. Multidisciplinary University Research Initiative. Swarms of Autonomous Robots and Mobile Sensors Projec

AquaOptical: a lightweight device for high-rate long-range underwater point-to-point communication

This paper describes AquaOptical, an underwater optical communication system. Three optical modems have been developed: a long range system, a short range system, and a hybrid. We describe their hardware and software architectures and highlight trade-offs. We present pool and ocean experiments with each system. In clear water AquaOptical was tested to achieve a data rate of 1.2 Mbit/sec at distances up to 30 m. The system was not tested beyond 30 m. In water with visibility estimated at 3 m AquaOptical achieved communication at data rates of 0.6 Mbit/sec at distances up to 9 m.Singapore. Defence Science & Technology Agenc

Adaptive Decentralized Control of Mobile Underwater Sensor Networks and Robots for Modeling Underwater Phenomena

Understanding the dynamics of bodies of water and their impact on the global environment requires sensing information over the full volume of water. In this article, we develop a gradient-based decentralized controller that dynamically adjusts the depth of a network of underwater sensors to optimize sensing for computing maximally detailed volumetric models. We prove that the controller converges to a local minimum and show how the controller can be extended to work with hybrid robot and sensor network systems. We implement the controller on an underwater sensor network with depth adjustment capabilities. Through simulations and in-situ experiments, we verify the functionality and performance of the system and algorithm. Keywords: depth adjustment; adaptive sensing; ocean; sensing; sensor networ