Wireless adhoc sensor and actuator networks on the farm

Agriculture accounts for a significant portion of the GDP in most developed countries. However, managing farms, particularly largescale extensive farming systems, is hindered by lack of data and increasing shortage of labour. We have deployed a large heterogeneous sensor network on a working farm to explore sensor network applications that can address some of the issues identified above. Our network is solar powered and has been running for over 6 months. The current deployment consists of over 40 moisture sensors that provide soil moisture profiles at varying depths, weight sensors to compute the amount of food and water consumed by animals, electronic tag readers, up to 40 sensors that can be used to track animal movement (consisting of GPS, compass and accelerometers), and 20 sensor/actuators that can be used to apply different stimuli (audio, vibration and mild electric shock) to the animal. The static part of the network is designed for 24/7 operation and is linked to the Internet via a dedicated high-gain radio link, also solar powered. The initial goals of the deployment are to provide a testbed for sensor network research in programmability and data handling while also being a vital tool for scientists to study animal behavior. Our longer term aim is to create a management system that completely transforms the way farms are managed.

Data collection, storage and retrieval with an underwater sensor network

In this paper we present a novel platform for underwater sensor networks to be used for long-term monitoring of coral reefs and �sheries. The sensor network consists of static and mobile underwater sensor nodes. The nodes communicate point-to-point using a novel high-speed optical communication system integrated into the TinyOS stack, and they broadcast using an acoustic protocol integrated in the TinyOS stack. The nodes have a variety of sensing capabilities, including cameras, water temperature, and pressure. The mobile nodes can locate and hover above the static nodes for data muling, and they can perform network maintenance functions such as deployment, relocation, and recovery. In this paper we describe the hardware and software architecture of this underwater sensor network. We then describe the optical and acoustic networking protocols and present experimental networking and data collected in a pool, in rivers, and in the ocean. Finally, we describe our experiments with mobility for data muling in this network.

Low-Cost vision-based AUV guidance system for reef navigation

Ensuring the long term viability of reef environments requires essential monitoring of many aspects of these ecosystems. However, the sheer size of these unstructured environments (for example Australia’s Great Barrier Reef pose a number of challenges for current monitoring platforms which are typically remote operated and required significant resources and infrastructure. Therefore, a primary objective of the CSIRO robotic reef monitoring project is to develop and deploy a large number of AUV teams to perform broadscale reef surveying. In order to achieve this, the platforms must be cheap, even possibly disposable. This paper presents the results of a preliminary investigation into the performance of a low-cost sensor suite and associated processing techniques for vision and inertial-based navigation within a highly unstructured reef environment.

Networked robots : flying robot navigation using a sensor net

This paper introduces the application of a sensor network to navigate a flying robot. We have developed distributed algorithms and efficient geographic routing techniques to incrementally guide one or more robots to points of interest based on sensor gradient fields, or along paths defined in terms of Cartesian coordinates. The robot itself is an integral part of the localization process which establishes the positions of sensors which are not known a priori. We use this system in a large-scale outdoor experiment with Mote sensors to guide an autonomous helicopter along a path encoded in the network. A simple handheld device, using this same environmental infrastructure, is used to guide humans.

Low-cost flight control system for a small autonomous helicopter

In this paper we describe a low-cost flight control system for a small (60 class) helicopter which is part of a larger project to develop an autonomous flying vehicle. Our approach differs from that of others in not using an expensive inertial/GPS sensing system. The primary sensors for vehicle stabilization are a low-cost inertial sensor and a pair of CMOS cameras. We describe the architecture of our flight control system, the inertial and visual sensing subsystems and present some flight control results.

A prototype system for the digital lodgement of spatial data

This dissertation develops the model of a prototype system for the digital lodgement of spatial data sets with statutory bodies responsible for the registration and approval of land related actions under the Torrens Title system. Spatial data pertain to the location of geographical entities together with their spatial dimensions and are classified as point, line, area or surface. This dissertation deals with a sub-set of spatial data, land boundary data that result from the activities performed by surveying and mapping organisations for the development of land parcels. The prototype system has been developed, utilising an event-driven paradigm for the user-interface, to exploit the potential of digital spatial data being generated from the utilisation of electronic techniques. The system provides for the creation of a digital model of the cadastral network and dependent data sets for an area of interest from hard copy records. This initial model is calibrated on registered control and updated by field survey to produce an amended model. The field-calibrated model then is electronically validated to ensure it complies with standards of format and content. The prototype system was designed specifically to create a database of land boundary data for subsequent retrieval by land professionals for surveying, mapping and related activities. Data extracted from this database are utilised for subsequent field survey operations without the need to create an initial digital model of an area of interest. Statistical reporting of differences resulting when subsequent initial and calibrated models are compared, replaces the traditional checking operations of spatial data performed by a land registry office. Digital lodgement of survey data is fundamental to the creation of the database of accurate land boundary data. This creation of the database is fundamental also to the efficient integration of accurate spatial data about land being generated by modem technology such as global positioning systems, and remote sensing and imaging, with land boundary information and other information held in Government databases. The prototype system developed provides for the delivery of accurate, digital land boundary data for the land registration process to ensure the continued maintenance of the integrity of the cadastre. Such data should meet also the more general and encompassing requirements of, and prove to be of tangible, longer term benefit to the developing, electronic land information industry.

Active power flow control in a distribution system using discontinuous voltage controller

stract This paper proposes a hybrid discontinuous control methodology for a voltage source converter (VSC), which is used in an uninterrupted power supply (UPS) application. The UPS controls the voltage at the point of common coupling (PCC). An LC filter is connected at the output of the VSC to bypass switching harmonics. With the help of both filter inductor current and filter capacitor voltage control, the voltage across the filter capacitor is controlled. Based on the voltage error, the control is switched between current and voltage control modes. In this scheme, an extra diode state is used that makes the VSC output current discontinuous. This diode state reduces the switching losses. The UPS controls the active power it supplies to a three-phase, four-wire distribution system. This gives a full flexibility to the grid to buy power from the UPS system depending on its cost and load requirement at any given time. The scheme is validated through simulation using PSCAD.

Solving navigational uncertainty using grid cells on robots

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments.

Implementation of an embedded sensor network for the coordination of Slocum gliders for coastal monitoring and observation

Autonomous Underwater Vehicles (AUVs) are revolutionizing oceanography through their versatility, autonomy and endurance. However, they are still an underutilized technology. For coastal operations, the ability to track a certain feature is of interest to ocean scientists. Adaptive and predictive path planning requires frequent communication with significant data transfer. Currently, most AUVs rely on satellite phones as their primary communication. This communication protocol is expensive and slow. To reduce communication costs and provide adequate data transfer rates, we present a hardware modification along with a software system that provides an alternative robust disruption- tolerant communications framework enabling cost-effective glider operation in coastal regions. The framework is specifically designed to address multi-sensor deployments. We provide a system overview and present testing and coverage data for the network. Additionally, we include an application of ocean-model driven trajectory design, which can benefit from the use of this network and communication system. Simulation and implementation results are presented for single and multiple vehicle deployments. The presented combination of infrastructure, software development and deployment experience brings us closer to the goal of providing a reliable and cost-effective data transfer framework to enable real-time, optimal trajectory design, based on ocean model predictions, to gather in situ measurements of interesting and evolving ocean features and phenomena.

Networked robotic sensor platform deployments for use in coastal environmental assessment in southern California

Mobile sensor platforms such as Autonomous Underwater Vehicles (AUVs) and robotic surface vessels, combined with static moored sensors compose a diverse sensor network that is able to provide macroscopic environmental analysis tool for ocean researchers. Working as a cohesive networked unit, the static buoys are always online, and provide insight as to the time and locations where a federated, mobile robot team should be deployed to effectively perform large scale spatiotemporal sampling on demand. Such a system can provide pertinent in situ measurements to marine biologists whom can then advise policy makers on critical environmental issues. This poster presents recent field deployment activity of AUVs demonstrating the effectiveness of our embedded communication network infrastructure throughout southern California coastal waters. We also report on progress towards real-time, web-streaming data from the multiple sampling locations and mobile sensor platforms. Static monitoring sites included in this presentation detail the network nodes positioned at Redondo Beach and Marina Del Ray. One of the deployed mobile sensors highlighted here are autonomous Slocum gliders. These nodes operate in the open ocean for periods as long as one month. The gliders are connected to the network via a Freewave radio modem network composed of multiple coastal base-stations. This increases the efficiency of deployment missions by reducing operational expenses via reduced reliability on satellite phones for communication, as well as increasing the rate and amount of data that can be transferred. Another mobile sensor platform presented in this study are the autonomous robotic boats. These platforms are utilized for harbor and littoral zone studies, and are capable of performing multi-robot coordination while observing known communication constraints. All of these pieces fit together to present an overview of ongoing collaborative work to develop an autonomous, region-wide, coastal environmental observation and monitoring sensor network.

A distributed protocol for object tracking in wireless multimedia sensor networks

We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

A navigating rat animat

This paper presents a new rat animat, a rat-sized bio-inspired robot platform currently being developed for embodied cognition and neuroscience research. The rodent animat is 150mm x 80mm x 70mm and has a different drive, visual, proximity, and odometry sensors, x86 PC, and LCD interface. The rat animat has a bio-inspired rodent navigation and mapping system called RatSLAM which demonstrates the capabilities of the platform and framework. A case study is presented of the robot's ability to learn the spatial layout of a figure of eight laboratory environment, including its ability to close physical loops based on visual input and odometry. A firing field plot similar to rodent 'non-conjunctive grid cells' is shown by plotting the activity of an internal network. Having a rodent animat the size of a real rat allows exploration of embodiment issues such as how the robot's sensori-motor systems and cognitive abilities interact. The initial observations concern the limitations of the deisgn as well as its strengths. For example, the visual sensor has a narrower field of view and is located much closer to the ground than for other robots in the lab, which alters the salience of visual cues and the effectiveness of different visual filtering techniques. The small size of the robot relative to corridors and open areas impacts on the possible trajectories of the robot. These perspective and size issues affect the formation and use of the cognitive map, and hence the navigation abilities of the rat animat.