Elliot S. Duff

Reactive navigation and opportunistic localization for autonomous underground mining vehicles

This paper describes an autonomous navigation system for a large underground mining vehicle. 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 paper briefly reviews absolute and relative navigation strategies, and describes an implementation of a reactive navigation system on a 30 tonne Load-Haul-Dump truck. This truck has achieved full-speed autonomous operation at an artificial test mine, and subsequently, at a operational underground mine.

The Development of a Telerobotic Rock Breaker

This paper describes the development of a tele-robotic rock breaker deployed at a mine over 1000kms from the remote operations centre. This distance introduces a number of technical and cognitive challenges to the design of the system, which have been addressed with the development of shared autonomy in the control system and a mixed reality user interface. A number of trials were conducted, culminating in a production field trial, which demonstrated that the system is safe, productive (sometimes faster) and integrates seamlessly with mine operations.

Robotic Explosive Charging in Mining and Construction Applications

This paper describes the development and testing of a robotic system for charging blast holes in underground mining. The automation system supports four main tactical functions: detection of blast holes; teleoperated arm pose control; automatic arm pose control; and human-in-the-loop visual servoing. We present the system architecture, and analyze the major components, Hole detection is crucial for automating the process, and we discuss theoretical and practical aspects in detail. The sensors used are laser range finders and cameras installed in the end effector. For automatic insertion, we consider image processing techniques to support visual servoing the tool to the hole. We also discuss issues surrounding the control of heavy-duty mining manipulators, in particular, friction, stiction, and actuator saturation.

Experiments in Autonomous Earth Moving

Abstract This paper presents a technology demonstrator currently under development and describes experiments carried out to date in autonomous bulk material handling using mobile equipment. Our primary platform is a Bobcat S185 skid-steer loader instrumented with an onboard computer, a sensor suite, and a communication link that support various levels of automation, from remote control to supervised autonomy. We present the main system components and discuss the autonomous cleaning of spillage and carryback, common bulk handling task in mining, currently executed exclusively using manually and/or remotely operated loaders. The system architecture is based on Spring, a Robotics Software Framework developed by CSIRO to support rapid development of new robotic systems, distributed as an Open Source package.

Vision-Based Navigational Competencies for a Car-like Vehicle

If mobile robots are to perform useful tasks in the real-world they will require a catalog of fundamental navigation competencies and a means to select between them. In this paper we describe our work on strongly vision-based competencies: road-following, person or vehicle following, pose and position stabilization. Results from experiments on an outdoor autonomous tractor, a car-like vehicle, are presented.

SAGE: Semantic Annotation of Georeferenced Environments

The emergence of portable 3D mapping systems are revolutionizing the way we generate digital 3D models of environments. These systems are human-centric and require the user to hold or carry the device while continuously walking and mapping an environment. In this paper, we adapt this unique coexistence of man and machines to propose SAGE (Semantic Annotation of Georeferenced Environments). SAGE consists of a portable 3D mobile mapping system and a smartphone that enables the user to assign semantic content to georeferenced 3D point clouds while scanning a scene. The proposed system contains several components including touchless speech acquisition, background noise adaptation, real time audio and vibrotactile feedback, automatic speech recognition, distributed clock synchronization, 3D annotation localization, user interaction, and interactive visualization. The most crucial advantage of SAGE technology is that it can be used to infer dynamic activities within an environment. Such activities are difficult to be identified with existing post-processing semantic annotation techniques. The capability of SAGE leads to many promising applications such as intelligent scene classification, place recognition and navigational aid tasks. We conduct several experiments to demonstrate the effectiveness of the proposed system.