Development of a System for Simulation and Control of an Unmanned Aerial Vehicle

Control systems of different vehicles such as helicopters, cars and boats have a lot in common. Thus, the main goal of this paper is to enable construction of a universal platform providing an opportunity of making such a system in a simplified and fast way. The designed platform operates in three different modes (SIL, MIX and HIL). The platform enables switching between different modes of operation without any changes implemented in a software layer. An embedded controller is able to schedule tasks without any delays, which involves utilization of a real-time operating system. Additionally, it is possible to remotely control and monitor the vehicle during its normal operation.     

Visual control of two aerial micro-robots by insect-based autopilots

In the framework of our research on biologically inspired microrobotics, we have developed two novel Automatic Flight Control Systems (AFCs): OCTAVE ( Optical flow Control sysTem for Aerospace VEhicles) and OSCAR ( Optical Scanning sensor for the Control of Autonomous Robots), both based on insects' visuomotor control systems. OCTAVE confers upon a tethered aerial robot (the OCTAVE robot) the ability to perform terrain following. OSCAR gives a tethered aerial robot (the OSCAR robot) the ability to fixate and track a contrasting target with a high level of accuracy. Both OCTAVE and OSCAR robots are based on optical velocity sensors, the principle of which is based on the results of previous electrophysiological studies on the fly's Elementary Motion Detectors (EMDs) performed at our laboratory. Both processing systems described are light enough to be mounted on-board Micro-Air Vehicles (MAVs) with an avionic payload small enough to be expressed in grams rather than kilograms.     

Forty-Sixth Annual Exhibition of the Institute of Physics and the Physical Society

Abstract

The frequency histogram of connected elements (FHCE) is a recently proposed algorithm that has successfully been applied in various medical image segmentation tasks. The FHCE is based on the idea that most pixels belong to the same class as their neighbouring pixels. However, the FHCE performance relies to a great extent on the optimal selection of a threshold parameter. Since evaluating segmentation results is a highly subjective process, a collection of threshold values must typically be examined. No algorithm has been proposed to automate the determination of the threshold parameter value of the FHCE. This study presents a method based on the fuzzy C-means clustering algorithm, designed to automatically generate optimal threshold values for the FHCE. This new approach was applied as a part of a structured sequence of image processing steps in order to facilitate segmentation of microcalcifications in digitized mammograms. A unique threshold value was generated for each mammogram, taking into account the different grey-level patterns based on different compositions of various breast tissues in it. The segmentation algorithm was tested on 100 mammograms (50 collected from the Mammographic Image Analysis Society and 50 normal mammograms onto which a number of simulated microcalcifications were generated). The algorithm was able to detect subtle microcalcifications with sensitivity ranging from 93 to 98%, False alarm ratio from 3 to 5% and false negatives variability from 2 to 3%.     

NANOIMPRINT LITHOGRAPHY TECHNOLOGY WITH AUTOMATIC ALIGNMENT

Nanoimprint lithography (NIL) is recognized as one of the most promising candidates for the next generation lithography (NGL) to obtain sub-100 nm patterns because of its simplicity, high-throughput and low-cost. While substantial effort has been expending on NIL for producing smaller and smaller feature sizes, considerably less effort has been devoted to the equally important issue—alignment between template and substrate. A homemade prototype nanoimprint lithography tool with a high precision automatic alignment system based on Moiré signals is presented. Coarse and fine pitch gratings are adopted to produce Moiré signals to control macro and micro actuators and enable the substrate to move towards the desired position automatically. Linear motors with 300 mm travel range and 1 μm step resolution are used as macro actuators, and piezoelectric translators with 50 μm travel range and 1 nm step resolution are used as micro actuators. In addition, the prototype provides one translation (z displacement) and two tilting motion(α and β ) to automatically bring uniform intact contact between the template and substrate surfaces by using a flexure stage. As a result, 10 μm coarse alignment accuracy and 20 nm fine alignment accuracy can be achieved. Finally, some results of nanostructures and micro devices such as nanoscale trenches and holes, gratings and microlens array fabricated using the prototype tool are presented, and hot embossing lithography, one typical NIL technology, are depicted by taking nanoscale gratings fabrication as an example.     

Genetic Programming-Based Automatic Gait Generation in Joint Space for a Quadruped Robot

This paper introduces a new approach to developing a fast gait for a quadruped robot using genetic programming (GP). Planning gaits for legged robots is a challenging task that requires optimizing parameters in a highly irregular and multi-dimensional space. Several recent approaches have focused on using genetic algorithms (GAs) to generate gaits automatically and have shown significant improvement over previous gait optimization results. Most current GA-based approaches optimize only a small, pre-selected set of parameters, but it is difficult to decide which parameters should be included in the optimization to get the best results. Moreover, the number of pre-selected parameters is at least 10, so it can be relatively difficult to optimize them, given their high degree of interdependence. To overcome these problems of the typical GA-based approach, we have proposed a seemingly more efficient approach that optimizes joint trajectories instead of locus-related parameters in Cartesian space, using GP. Our GP-based method has obtained much-improved results over the GA-based approaches tested in experiments on the Sony AIBO ERS-7 in the Webots environment. The elite archive mechanism is introduced to combat the premature convergence problems in GP and has shown better results than a traditional multi-population approach.