Automated bolting and meshing on a continuous miner for roadway development

Automated installation of primary roof support material can potentially increase productivity and operator safety in the roadway development process within underground coal mining. Although the broader manufacturing sector has benefited from automation, several challenges exist within the Australian underground coal industry which makes it difficult to fully exploit these technologies. At the University of Wollongong a series of reprogrammable electromechanical manipulators have been designed to overcome these challenges and automatically handle the installation of roof and rib containment consumables on a continuous miner. The automated manipulation removes personnel from hazards in the immediate face area, particularly those associated with working in a confined and unstable working environment in close proximity to rotating and moving equipment. In a series of above ground trials the automated system was successfully demonstrated without human intervention and proven to be capable of achieving cycle times at a rate of 10 m per operating hour, consistent with that required to support high capacity longwall mines. The trials also identified a number of refinements which could further improve both cycle times and system reliability when considering the technology for underground use. The results have concluded that conventional manual handling practices on a continuous miner can be eliminated, and that the prototypes have significantly reduced the technical risk in proceeding to a full underground trial.

Learning Robotic Hand-eye Coordination Through a Developmental Constraint Driven Approach

The skill of robotic hand-eye coordination not only helps robots to deal with real time environment,but also afects the fundamental framework of robotic cognition.A number of approaches have been developed in the literature for construction of the robotic hand-eye coordination.However,several important features within infant developmental procedure have not been introduced into such approaches.This paper proposes a new method for robotic hand-eye coordination by imitating the developmental progress of human infants.The work employs a brain-like neural network system inspired by infant brain structure to learn hand-eye coordination,and adopts a developmental mechanism from psychology to drive the robot.The entire learning procedure is driven by developmental constraint： The robot starts to act under fully constrained conditions,when the robot learning system becomes stable,a new constraint is assigned to the robot.After that,the robot needs to act with this new condition again.When all the contained conditions have been overcome,the robot is able to obtain hand-eye coordination ability.The work is supported by experimental evaluation,which shows that the new approach is able to drive the robot to learn autonomously,and make the robot also exhibit developmental progress similar to human infants.

Towards Efficient Robotic Software Development by Reusing Behavior Tree Structures for Task Planning Paradigms

interaction pipelines while maintaining interfaces for task-specific customization.The Structural-BT framework supports the modular design of structure functionalities and allows easy extensibility of the inner planning flows between BT components.With the Structural-BT framework,software engineers can develop robotic software by flexibly composing BT structures to formulate the skeleton software architecture and implement task-specific algorithms when necessary.In the experiment,this paper develops robotic software for diverse task scenarios and selects the baseline approaches of Robot Operating System(ROS)and classical BT development frameworks for comparison.By quantitatively measuring the reuse frequencies and ratios of BT structures,the Structural-BT framework has been shown to be more efficient than the baseline approaches for robotic software development.