Frazer K. Noble

Do RSSI values reliably map to RSS in a localization system

In recent years, research into localization systems has become more popular as the proliferation of Wireless Sensor Networks (WSNs) grows. Wireless Localization can refer to either an “Active” system which tracks a mobile transceiver, or “Passive” localization which tracks a transceiver free entity by measuring the changes it makes to the surrounding wireless environment. Recent work has seen both of these systems implemented with Received Signal Strength Indication (RSSI) values from transceivers. Many algorithms and channel models have been presented to increase the accuracy of a Received Signal Strength (RSS) based system. In this paper we experimentally check whether RSSI values map to the expected RSS values within an IEEE 802.15.4 network. Indoor experiments are repeated within an ideal outdoor environment, with multiple device platforms, to eliminate indoor multipath propagation as the cause for inconsistent behavior of RSSI. We identify 3 key issues with raw RSSI values and present either a possible solution or a mitigation strategy to reduce their effect. We conclude that using raw RSSI values is flawed, as the premise that they uniquely map to the distance between transceivers is incorrect. However they may be calibrated to increase their accuracy, and therefore viability.

Comparison of OpenCV's feature detectors and feature matchers

There exists a range of feature detecting and feature matching algorithms; many of which have been included in the Open Computer Vision (OpenCV) library. However, given these different tools, which one should be used? This paper discusses the implementation and comparison of a range of the librarys feature detectors and feature matchers. It shows that the Speeded-Up Robust Features (SURF) detector found the greatest number of features in an image, and that the Brute Force (BF) matcher matched the greatest number of detected features in an image pair. Given a benchmark image set, OpenCVs SURF detector found, on average, 1907.20 features in 1538.61 ms, and OpenCVs BF matcher, on average, matched features in 160.24 ms. The combination of the Binary Robust Invariant Scalable Key-points (BRISK) detector and BF matcher was found to be the highest ranked combination of OpenCVs feature detectors and feature matchers; on average, detecting and matching 1132.00 and 80.20 features, respectively, in 265.67 ms. It was concluded that if the number of features detected is important, the SURF detector should be used; else, if the number of features matched is important, the BF matcher should be used; otherwise, the combination of the OpenCVs BRISK feature detector and BF feature matcher should be used.

Design of end-effectors for a chemistry automation plant

In typical chemistry experiments, there are many manual processes; chemistry automation is the process of automating these. In this paper, we describe work done to develop end-effectors that extend current capabilities of chemistry automation plants. The hierarchy established, the design process employed, and four end-effectors: the “Claw”, “Balloon”, “Cross”, and “Band” are presented, described, and discussed. The Claw, Balloon, and Band end-effectors were able to successfully pick-and-place bottles with diameters between 10 and 30 mm. Evaluating the designs, the Band end-effector was chosen as the working solution for use in future work.

Entity tracking within a Zigbee based smart home

Modern Smart Home Automation (SMA) systems are predominantly based on wireless communication standards. New home automation setups can often include dozens of devices ranging from thermostats, humidity sensors, light switches, digital locks and cooling systems, all communicating on a common network. In this paper we focus on how SMA systems built on one of the most common standards (Zigbee), could be leveraged to provide a secondary benefit in the form of an Indoor Positioning System (IPS). IPS can be implemented in the form of Device Free Localization (DfL), Active tracking or as a combination of both techniques. A system containing a DfL implementation can detect and track moving entities by monitoring the changes in received signal strength (RSSI) values between nodes within a wireless network. DfL does not require the entity that is being tracked to carry an electronic device and actively contribute to the localization process. In Active tracking, the tracked entity contributes to the tracking process. In this paper both techniques are implemented individually, and a combination of both techniques is explored. Having implemented DfL and Active tracking, we were able to localize a person within a 3m × 3m quadrant with DfL with 80% accuracy. Active tracking resulted in a higher resolution of tracking compared to DfL, being able to localize a person within a 2m × 2m area with 95% accuracy. The accuracy of Active Tracking was then further increased to 98%, by coupling Active Tracking with DfL measurements.

A Colour Detection and Connected-Objects Separation Methodology for VEX Robotics

One of the issues associated with programming a VEX Robotics Competition (VRC) robot for the autonomous period is providing it with enough information regarding its environment so that it can move about the field intelligently. As such, an objective of our research was to develop a series of machine vision tools so that a VRC robot could identify VRC field elements, other robots, and field perimeters; responding appropriately. We have carried out a review of relevant literature and identified a number of algorithms, image processing tools, and control paradigms, as well as, developed our own approaches, which we have implemented in C++ using the OpenCV library. Here we present the results of our initial efforts, namely our implemented colour identification, connected-object separation, and multiple connected-objects separation methodologies.

Modeling and Simulation of a Bio-Mimetic, Antagonistically Actuated, Limb Joint

Wearable assistive devices’ (WADs) development is impeded by traditional actuators’ and control paradigms’ lack of compliance and adaptability; as such, the central nervous system’s (CNS) actuation and control principles have been investigated in order to overcome these limitations in a novel way. A bio-mimetic model of a limb joint, which is antagonistically actuated by two Hill-type muscles, is presented. Limb joint stability and transient response, as functions of co-activation, have been investigated. Three simulations have been carried out: equal (Af(f,f)), unequal (Af(3,f)), and differential (Af(3,Ramp(g))) co-activation. For normalized stimulus frequency range: 1 ≤ f ≤ 3, equal and unequal co-activation leads to increased limb joint damping and reduced transient oscillation. For the equally/unequally co-activated case, the linearized model’s dominant complex-conjugate poles become increasingly negative and tend towards the real axis, which indicate that increased co-activation leads to increased joint stability. With respect to differential co-activation, increasing the limb joint’s antagonistic muscle’s normalized stimulus frequency’s (f) rate of change (g) leads to increased angular velocity (ω); however, at a cost of increased overshoot. Differential activation of the antagonistic muscle results in positive angular rotation (Θ).Copyright