EPID-18. Accuracy of claims-based algorithms in the identification of leptomeningeal disease: a validation study

A Novel Laminar Jamming Mechanism for Variable-Stiffness Robotic Arms

Two Heads Are Better Than One: Collaborative LLM Embodied Agents for Human-Robot Interaction

Guide-LLM: An Embodied LLM Agent and Text-Based Topological Map for Robotic Guidance of People with Visual Impairments

Design Principles for Safe Human Robot Collaboration.

A Review of Mechanisms to Vary the Stiffness of Laminar Jamming Structures and Their Applications in Robotics

Comparison of strength profile representations using musculoskeletal models and their applications in robotics

Towards Smart Green Wall Maintenance and Wallbot Technology

The wallbot: A low-cost robot for green wall inspection.

The Green Wallbot - City of Sydney Environmental Grant Project Report

A model-based assistance-as-needed paradigm has been developed to govern the assistance provided by an assistive robot to its operator. This paradigm has advantages over existing methods of providing assistance-as-needed for applications such as robotic rehabilitation. However, implementation of the model-based paradigm requires a control scheme to be developed which controls the robot so as to provide the assistance calculated by the model-based paradigm to its operator. In this paper an admittance control scheme for providing model-based assistance-as-needed is presented. It is developed considering its suitability for human-robot interaction, and its role within the model-based assistance-as-needed framework. Results from the control implemented on an example robot showed it is capable of providing the operator with the desired level of assistance as governed by the model-based paradigm. This is an essential requirement for the paradigm to be capable of providing efficacious assistance-as-needed in applications such as robotic rehabilitation.

A framework for singularity-robust manipulator control during physical human-robot interaction

Admittance control scheme for implementing model-based assistance-as-needed on a robot

Estimating physical assistance need using a musculoskeletal model

We present the ANBOT, an intelligent robotic coworker for physical human-robot collaboration. The ANBOT system assists workers performing industrial abrasive blasting, shielding them from the large forces experienced during this physically demanding task. The co-operative robotic system combines the strength and endurance of robots with the decision making of skilled workers. The inherent challenges in human-robot collaboration, combined with the difficult blasting environment required novel design decisions to be made and new solutions to be developed. These include an approach for handling kinematic singularities in a manner suitable for human-robot co-operation, estimating worker pose under poor visibility conditions, and an intuitive control scheme that adapts the robotic assistance based on the estimated strength of the worker. In this work we summarise the ANBOT system and present findings from preliminary site trials. The trials included several real industrial blasting tasks under the control of a skilled abrasive blasting worker who had no experience working alongside a robot. Results demonstrate the suitability of the ANBOT for practical industrial applications.

Next-Generation Intelligent Robotic Mobility Aid for Vision Impaired People

5G Connected Cobots

ARC Training Centre for Collaborative Robotics in Advanced Manufacturing