Toward Rapid Prototyping of Miniature Capsule Robots

Minimally invasive robotic surgery techniques are becoming popular thanks to their enhanced patient benefits, including shorter recovery time, better cosmetic results and reduced discomforts. Less invasive procedures would be achieved with the use of Medical Capsule Robots (MCRs). These devices are characterized by low power requirements and small dimensions as well as uncompromising safety. MCRs operate wirelessly in abdominal Minimally Invasive Surgery (MIS) and Natural Orifice Transluminal Endoscopic Surgery (NOTES) or in the Gastrointestinal (GI) tract. The design process of MCRs, however, is expensive and time consuming. A platform for rapid prototyping MCRs is needed so that MCR researchers can reduce development costs and spend more time in studying innovative MCR applications. In this work, we introduce an open source modular platform geared toward rapid prototyping MCRs. To speed up the prototyping process, the MCR is programmed using TinyOS instead of bare-bone C. We present the hardware architecture of the platform, and the motivation for using TinyOS. To show the viability of TinyOS, we present results from an experiment involving sensing, actuation and wireless communication. This work lays the foundation for our future goal of building an integrated design environment for the design, analysis and simulation of MCRs

Systematic Design of edical Capsule Robots

Medical capsule robots that navigate inside the body as diagnostic and interventional tools are an emerging and challenging research area within medical CPSs. These robots must provide locomotion, sensing, actuation, and communication within severe size, power, and computational constraints. This paper presents the first effort for an open architecture, platform design, software infrastructure, and a supporting modular design environment for medical capsule robots to further this research area

Web-based Integrated Development Environment for Event-Driven Applications

Event-driven programming is a popular methodology for the development of resource-constrained embedded systems. While it is a natural abstraction for applications that interface with the physical world, the disadvantage is that the control flow of a program is hidden in the maze of event handlers and call-back functions. TinyOS is a representative event-driven operating system, designed for wireless sensor networks, featuring a component-based architecture that promotes code reuse. In this paper, we present a web-based model-driven graphical design environment for TinyOS that visualizes the component hierarchy of an application, and captures its eventbased scheduling mechanism. In contrast with existing visual environments, our representation explicitly captures the control flow of the application through events and commands, which makes it easier to understand the program logic than studying the source code. The design environment supports two-way code generation: mapping the visual representation to TinyOS source code, as well as building visual models from existing sources

Shooter localization and weapon classification with soldier-wearable networked sensors

The paper presents a wireless sensor network-based mobile countersniper system. A sensor node consists of a helmetmounted microphone array, a COTS MICAz mote for internode communication and a custom sensorboard that implements the acoustic detection and Time of Arrival (ToA) estimation algorithms on an FPGA. A 3-axis compass provides self orientation and Bluetooth is used for communication with the soldier’s PDA running the data fusion and the user interface. The heterogeneous sensor fusion algorithm can work with data from a single sensor or it can fuse ToA or Angle of Arrival (AoA) observations of muzzle blasts and ballistic shockwaves from multiple sensors. The system estimates the trajectory, the range, the caliber and the weapon type. The paper presents the system design and the results from an independent evaluation at the US Army Aberdeen Test Center. The system performance is characterized by 1-degree trajectory precision and over 95 % caliber estimation accuracy for all shots, and close to 100 % weapon estimation accuracy for 4 out of 6 guns tested

Multi-Modal Target Tracking Using Heterogeneous Sensor Networks

Abstract—The paper describes a target tracking system run-ning on a Heterogeneous Sensor Network (HSN) and presents results gathered from a realistic deployment. The system fuses audio direction of arrival data from mote class devices and object detection measurements from embedded PCs equipped with cameras. The acoustic sensor nodes perform beamforming and measure the energy as a function of the angle. The camera nodes detect moving objects and estimate their angle. The sensor detections are sent to a centralized sensor fusion node via a combination of two wireless networks. The novelty of our system is the unique combination of target tracking methods customized for the application at hand and their implementation on an actual HSN platform. I