Helicopter automation using a low-cost sensing system

This paper details the design of an autonomous helicopter control system using a low cost sensor suite. Control is maintained using simple nested PID loops. Aircraft attitude, velocity, and height is estimated using an in-house designed IMU and vision system. Information is combined using complimentary filtering. The aircraft is shown to be stabilised and responding to high level demands on all axes, including heading, height, lateral velocity and longitudinal velocity.

Partial automation of database processing of simulation outputs from L-systems models of plant morphogenesis

Models of plant architecture allow us to explore how genotype environment interactions effect the development of plant phenotypes. Such models generate masses of data organised in complex hierarchies. This paper presents a generic system for creating and automatically populating a relational database from data generated by the widely used L-system approach to modelling plant morphogenesis. Techniques from compiler technology are applied to generate attributes (new fields) in the database, to simplify query development for the recursively-structured branching relationship. Use of biological terminology in an interactive query builder contributes towards making the system biologist-friendly. (C) 2002 Elsevier Science Ireland Ltd. All rights reserved.

Towards rope shovel automation operation information system

The road to electric rope shovel automation is marked with technological innovations that include an increase in operational information available to mining operations. The CRCMining Shovel Operator Information System not only collects machine operational data but also provides the operator with knowledge-of-performance and influences his/her performance to achieve higher productivity with reduced machine duty. The operator’s behaviour is one of the most important aspects of the man-machine interaction to be considered before semi- or fully-automated shovel systems can be realised. This paper presents the results of the rope shovel studies conducted by CRCMining between 2002 and 2004, provides information on current research to improve shovel performance and briefly discusses the implications of human-system interactions on future designs of autonomous machines.

Experiments in outdoor operation of RatSLAM

This paper shows initial results in deploying the biologically inspired Simultaneous Localisation and Mapping system, RatSLAM, in an outdoor environment. RatSLAM has been widely tested in indoor environments on the task of producing topologically coherent maps based on a fusion of odometric and visual information. This paper details the changes required to deploy RatSLAM on a small tractor equipped with odometry and an omnidirectional camera. The principal changes relate to the vision system, with others required for RatSLAM to use omnidirectional visual data. The initial results from mapping around a 500 m loop are promising, with many improvements still to be made.

A global vision system for a robot soccer team

This paper describes the real time global vision system for the robot soccer team the RoboRoos. It has a highly optimised pipeline that includes thresholding, segmenting, colour normalising, object recognition and perspective and lens correction. It has a fast ‘paint’ colour calibration system that can calibrate in any face of the YUV or HSI cube. It also autonomously selects both an appropriate camera gain and colour gains robot regions across the field to achieve colour uniformity. Camera geometry calibration is performed automatically from selection of keypoints on the field. The system acheives a position accuracy of better than 15mm over a 4m × 5.5m field, and orientation accuracy to within 1°. It processes 614 × 480 pixels at 60Hz on a 2.0GHz Pentium 4 microprocessor.

A modified particle filter for simultaneous robot localization and landmark tracking in an indoor environment

This paper presents the implementation of a modified particle filter for vision-based simultaneous localization and mapping of an autonomous robot in a structured indoor environment. Through this method, artificial landmarks such as multi-coloured cylinders can be tracked with a camera mounted on the robot, and the position of the robot can be estimated at the same time. Experimental results in simulation and in real environments show that this approach has advantages over the extended Kalman filter with ambiguous data association and various levels of odometric noise.