On the Development of an Automated Design Procedure to Design Optimal Robots

The objective in this work is to build a rapid and automated numerical design method that makes optimal design of robots possible. In this work, two classes of optimal robot design problems were specifically addressed: (1) When the objective is to optimize a pre-designed robot, and (2) when the goal is to design an optimal robot from scratch. In the first case, to reach the optimum design some of the critical dimensions or specific measures to optimize (design parameters) are varied within an established range. Then the stress is calculated as a function of the design parameter(s), the design parameter(s) that optimizes a pre-determined performance index provides the optimum design. In the second case, this work focuses on the development of an automated procedure for the optimal design of robotic systems. For this purpose, Pro/Engineer© and MatLab© software packages are integrated to draw the robot parts, optimize them, and then re-draw the optimal system parts.

Visual control of robots : high-performance visual servoing

The application of high-speed machine vision for close-loop position control, or visual servoing, of a robot manipulator. It provides a comprehensive coverage of all aspects of the visual servoing problem: robotics, vision, control, technology and implementation issues. While much of the discussion is quite general the experimental work described is based on the use of a high-speed binary vision system with a monocular "eye-in-hand" camera.

Automation of an underground mining vehicle using reactive navigation and opportunistic localization

This paper describes the implementation of an autonomous navigation system onto a 30 tonne Load-Haul-Dump truck. The control architecture is based on a robust reactive wall-following behaviour. To make it purposeful we provide driving hints derived from an approximate nodal-map. For most of the time, the vehicle is driven with weak localization (odometry). This need only be improved at intersections where decisions must be made - a technique we refer to as opportunistic localization. The truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

Validation and automation of the DYNJAWS component module of the BEAMnrc Monte Carlo code

The purpose of this work is to validate and automate the use of DYNJAWS; a new component module (CM) in the BEAMnrc Monte Carlo (MC) user code. The DYNJAWS CM simulates dynamic wedges and can be used in three modes; dynamic, step-and-shoot and static. The step-and-shoot and dynamic modes require an additional input file defining the positions of the jaw that constitutes the dynamic wedge, at regular intervals during its motion. A method for automating the generation of the input file is presented which will allow for the more efficient use of the DYNJAWS CM. Wedged profiles have been measured and simulated for 6 and 10 MV photons at three field sizes (5 cm x 5 cm , 10 cm x10 cm and 20 cm x 20 cm), four wedge angles (15, 30, 45 and 60 degrees), at dmax and at 10 cm depth. Results of this study show agreement between the measured and the MC profiles to within 3% of absolute dose or 3 mm distance to agreement for all wedge angles at both energies and depths. The gamma analysis suggests that dynamic mode is more accurate than the step-and-shoot mode. The DYNJAWS CM is an important addition to the BEAMnrc code and will enable the MC verification of patient treatments involving dynamic wedges.

The automation of radiotherapy treatment planning assessment

Aim The assessment of treatment plans is an important component in the education of radiation therapists. The establishment of a grade for a plan is currently based on subjective assessment of a range of criteria. The automation of assessment could provide a number of advantages including faster feedback, reduced chance of human error, and simpler aggregation of past results. Method A collection of treatments planned by a cohort of 27 second year radiation therapy students were selected for quantitative evaluation. Treatment sites included the bladder, cervix, larynx, parotid and prostate, although only the larynx plans had been assessed in detail. The plans were designed with the Pinnacle system and exported using the DICOM framework. Assessment criteria included beam arrangement optimisation, volume contouring, target dose coverage and homogeneity, and organ-at-risk sparing. The in-house Treatment and Dose Assessor (TADA) software1 was evaluated for suitability in assisting with the quantitative assessment of these plans. Dose volume data were exported in per-student and per-structure data tables, along with beam complexity metrics, dose volume histograms, and reports on naming conventions. Results The treatment plans were exported and processed using TADA, with the processing of all 27 plans for each treatment site taking less than two minutes. Naming conventions were successfully checked against a reference protocol. Significant variations between student plans were found. Correlation with assessment feedback was established for the larynx plans. Conclusion The data generated could be used to inform the selection of future assessment criteria, monitor student development, and provide useful feedback to the students. The provision of objective, quantitative evaluations of plan quality would be a valuable addition to not only radiotherapy education programmes but also for staff development and potentially credentialing methods. New functionality within TADA developed for this work could be applied clinically to, for example, evaluate protocol compliance.

Automation of underground LHD and truck haulage

This paper reviews the state-of-the-art in the automation of underground mining vehicles and reports on the development of an autonomous navigation system under development through the CMTE with sponsorship arranged by AMIRA. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are discussed. The auto-guidance system being developed overcomes some of the limitations of state-of-the-art prototype æcommercialÆ systems. It can be retrofitted to existing remote controlled vehicles, uses minimum installed infrastructure and is flexible enough for rapid relocation to alternate routes. The navigation techniques use data fusion of two separate sets of sensors combining natural feature recognition, nodal maps and inertial navigation techniques. Collision detection is incorporated and people and other traffic are excluded from the tramming area. This paper describes the work being done by the group with regard to auto-tramming and also outlines the future goals.

Automation of underground truck haulage

This paper reviews the state-of-the art in the automation of underground truck haulage. Past attemps at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tram...

Automation of underground truck haulage

This paper reviews the state-of-the-art in the automation of underground truck haulage. Past attempts at automating LHDs and haul trucks are described and their particular strengths and weaknesses are listed. We argue that the simple auto-tramming systems currently being commercialised, that follow rail-type guides placed along the back, cannot match the performance, flexibility and reliability of systems based on modern mobile robotic principles. In addition, the lack of collision detection research in the underground environment is highlighted.

Automation of Chemical Spray Pyrolysis Unit and Fabrication of Sprayed CuInS2/In2S3 Solar Cell

Aim of the present work was to automate CSP process, to deposit and characterize CuInS2/In2S3 layers using this system and to fabricate devices using these films.An automated spray system for the deposition of compound semiconductor thin films was designed and developed so as to eliminate the manual labour involved in spraying and facilitate standardization of the method. The system was designed such that parameters like spray rate, movement of spray head, duration of spray, temperature of substrate, pressure of carrier gas and height of the spray head from the substrate could be varied. Using this system, binary, ternary as well as quaternary films could be successfully deposited.The second part of the work deal with deposition and characterization of CuInS2 and In2S3 layers respectively.In the case of CuInS2 absorbers, the effects of different preparation conditions and post deposition treatments on the optoelectronic, morphological and structural properties were investigated. It was observed that preparation conditions and post deposition treatments played crucial role in controlling the properties of the films. The studies in this direction were useful in understanding how the variation in spray parameters tailored the properties of the absorber layer. These results were subsequently made use of in device fabrication process.Effects of copper incorporation in In2S3 films were investigated to find how the diffusion of Cu from CuInS2 to In2S3 will affect the properties at the junction. It was noticed that there was a regular variation in the opto-electronic properties with increase in copper concentration.Devices were fabricated on ITO coated glass using CuInS2 as absorber and In2S3 as buffer layer with silver as the top electrode. Stable devices could be deposited over an area of 0.25 cm2, even though the efficiency obtained was not high. Using manual spray system, we could achieve devices of area 0.01 cm2 only. Thus automation helped in obtaining repeatable results over larger areas than those obtained while using the manual unit. Silver diffusion on the cells before coating the electrodes resulted in better collection of carriers.From this work it was seen CuInS2/In2S3 junction deposited through automated spray process has potential to achieve high efficiencies.

Learning and adaptation in physical heterogeneous teams of robots

In this paper we present a novel approach to assigning roles to robots in a team of physical heterogeneous robots. Its members compete for these roles and get rewards for them. The rewards are used to determine each agent’s preferences and which agents are better adapted to the environment. These aspects are included in the decision making process. Agent interactions are modelled using the concept of an ecosystem in which each robot is a species, resulting in emergent behaviour of the whole set of agents. One of the most important features of this approach is its high adaptability. Unlike some other learning techniques, this approach does not need to start a whole exploitation process when the environment changes. All this is exemplified by means of experiments run on a simulator. In addition, the algorithm developed was applied as applied to several teams of robots in order to analyse the impact of heterogeneity in these systems