A Framework of Hybrid Force/Motion Skills Learning for Robots

Human factors and human-centred design philosophy are highly desired in today’s robotics applications such as human-robot interaction (HRI). Several studies showed that endowing robots of human-like interaction skills can not only make them more likeable but also improve their performance. In particular, skill transfer by imitation learning can increase usability and acceptability of robots by the users without computer programming skills. In fact, besides positional information, muscle stiffness of the human arm, contact force with the environment also play important roles in understanding and generating human-like manipulation behaviours for robots, e.g., in physical HRI and tele-operation. To this end, we present a novel robot learning framework based on Dynamic Movement Primitives (DMPs), taking into consideration both the positional and the contact force profiles for human-robot skills transferring. Distinguished from the conventional method involving only the motion information, the proposed framework combines two sets of DMPs, which are built to model the motion trajectory and the force variation of the robot manipulator, respectively. Thus, a hybrid force/motion control approach is taken to ensure the accurate tracking and reproduction of the desired positional and force motor skills. Meanwhile, in order to simplify the control system, a momentum-based force observer is applied to estimate the contact force instead of employing force sensors. To deploy the learned motion-force robot manipulation skills to a broader variety of tasks, the generalization of these DMP models in actual situations is also considered. Comparative experiments have been conducted using a Baxter Robot to verify the effectiveness of the proposed learning framework on real-world scenarios like cleaning a table

Making a financial time machine:a multitouch application to enable interactive 3-D visualization of distant savings goals

Financial planning and decision making for the general public continues to vex and perplex in equal measure. Whilst the tools presented by a typical desktop computer should make the task easier, the recent financial crisis confirms the increasing difficulty that people have in calculating the benefits of deferring consumption for future gains (i.e. Saving). We present an interactive concept demonstration for Microsoft SurfaceTM that tackles two of the key barriers to saving decision making. Firstly we show an interface that avoid the laborious writing down or inputting of data and instead embodies the cognitive decision of allocation of resources in a physical gesture based interface, where the scale of the investment or expenditure correlates with the scale of the gesture. Second we show how a fast-forward based animation can demonstrate the impact of small increments in savings to a long term savings goal in a strategy game-based, interactive format. The platform uses custom software (XNATM format) as opposed to the more usual WPFTM format found on Surface applications. This enables dynamic 3-D graphical icons to be used to maximize the interactive appeal of the interface. Demonstration and test trial feedback indicates that this platform can be adapted to suit the narrative of individual purchasing decisions to inform educate diverse user groups about the long term consequences of small financial decisions

Human-Machine Interface for Remote Training of Robot Tasks

Regardless of their industrial or research application, the streamlining of robot operations is limited by the proximity of experienced users to the actual hardware. Be it massive open online robotics courses, crowd-sourcing of robot task training, or remote research on massive robot farms for machine learning, the need to create an apt remote Human-Machine Interface is quite prevalent. The paper at hand proposes a novel solution to the programming/training of remote robots employing an intuitive and accurate user-interface which offers all the benefits of working with real robots without imposing delays and inefficiency. The system includes: a vision-based 3D hand detection and gesture recognition subsystem, a simulated digital twin of a robot as visual feedback, and the "remote" robot learning/executing trajectories using dynamic motion primitives. Our results indicate that the system is a promising solution to the problem of remote training of robot tasks.Comment: Accepted in IEEE International Conference on Imaging Systems and Techniques - IST201

Remote Access to a Prototyping Laboratory

There is a growing global demand for continuing adult higher education particularly in science and engineering subjects. New technologies are emerging which would enable the development of a Remote Access Laboratory for rapid prototyping of Artificial Intelligence, as a learning environment for mechatronic engineering, in which high precision electromechanical devices are designed to exhibit autonomous behaviour. Secondary research investigated the learning theories for a Remote Access Laboratory, and the current practices for distance learning, involving groupware in shared activity 'collaboratories'. Having determined that the laboratory would need a multi-user interactive environment architecture, with the requirement for adaptability to rapid developments,a distributed software architecture was selected. The laboratory design was subsequently argued to be best served by Intelligent Agents in a Multi-Agent system. The aims of the research were to establish the viability of a Remote Access Laboratory for mechatronic experimentation, and to evaluate the technologies required to implement such a laboratory environment for rapid prototyping. These were achieved by developing a novel user interface, based on a multi-functional screen layout, and a graphical specification facility to provide robotic navigation that is intuitive to use and does not require text-based programming. The research investigated the prototyping of robotic behaviour, which used Programming by Demonstration as an innovative technique to prototype robot navigation. The method of designing behaviours met an anticipated need to allow the robot to interact with an environment, to achieve goals under conditions of uncertainty, while requiring a level of abstraction in the behaviour design. The interface structured a composite of the designed behaviours into prototype Artificial Intelligence using a hierarchical behaviour architecture, which complied with the principles of Object Orientated programming. This was subsequently a new and original programming method to facilitate rapid prototyping of Artificial Intelligence design and structuring. Experimentation involved 20 participants attempting to accomplish a series of tasks which involved using the prototyped interface and an existing text-based robot programming system. The participants were profiled by their formal qualifications, knowledge and experience. The experimental data obtained were used to establish a comparative measure of the prototype interface success compared with an existing distance-learning, home experiment kit, in the form of a small controllable model vehicle. The data obtained provided strong evidence to support the hypothesis that a Programming by Demonstration based system for rapid prototyping is more flexible and easier to use than a previously existing distance learning text-based system. The Programming by Demonstration system showed great promise, being quicker for prototyping, and more intuitive. The learning interface design pioneered new techniques and technologies for rapid prototyping of Artificial Intelligence in a Mechatronics Remote Access Laboratory

A NPC Behaviour Definition System for Use by Programmers and Designers

In this paper we describe ZBL/0, a scripting system for defining NPC (Non Player Character) behaviour in FPS (First Person Shooter) games. ZBL/0 has been used to illustrate the use of scripting systems in computer games in general and the scripting of NPC behaviour in particular in the context of a book on game development. Many novice game designers have clear ideas about how the computer game they imagine should work but have little knowledge – if any – about how their ideas can be implemented. This is why books on game creation (design, programming etc.), as well as all-in-one game creation systems – especially designed for ease of use and intended for an amateur audience – enjoy great popularity. A large proportion of these books however merely present solutions in the form of descriptions and explanations of specific implementations with inadequate explanations of principles. While this may benefit rapid application development it often does not lead to a deeper understanding of the underlying concepts. The understanding of rule-based behaviour definition through simple scripting in computer games and the development of such scripts by programmers and designers is what we aim to address with the ZBL/0 system

Enhancing Clinical Learning Through an Innovative Instructor Application for ECMO Patient Simulators

© 2018 The Authors. Reprinted by permission of SAGE PublicationsBackground. Simulation-based learning (SBL) employs the synergy between technology and people to immerse learners in highly-realistic situations in order to achieve quality clinical education. Due to the ever-increasing popularity of extracorporeal membrane oxygenation (ECMO) SBL, there is a pressing need for a proper technological infrastructure that enables high-fidelity simulation to better train ECMO specialists to deal with related emergencies. In this article, we tackle the control aspect of the infrastructure by presenting and evaluating an innovative cloud-based instructor, simulator controller, and simulation operations specialist application that enables real-time remote control of fullscale immersive ECMO simulation experiences for ECMO specialists as well as creating custom simulation scenarios for standardized training of individual healthcare professionals or clinical teams. Aim. This article evaluates the intuitiveness, responsiveness, and convenience of the ECMO instructor application as a viable ECMO simulator control interface. Method. A questionnaire-based usability study was conducted following institutional ethical approval. Nineteen ECMO practitioners were given a live demonstration of the instructor application in the context of an ECMO simulator demonstration during which they also had the opportunity to interact with it. Participants then filled in a questionnaire to evaluate the ECMO instructor application as per intuitiveness, responsiveness, and convenience. Results. The collected feedback data confirmed that the presented application has an intuitive, responsive, and convenient ECMO simulator control interface. Conclusion. The present study provided evidence signifying that the ECMO instructor application is a viable ECMO simulator control interface. Next steps will comprise a pilot study evaluating the educational efficacy of the instructor application in the clinical context with further technical enhancements as per participants’ feedback.Peer reviewedFinal Accepted Versio

Multi-Modal Human-Machine Communication for Instructing Robot Grasping Tasks

A major challenge for the realization of intelligent robots is to supply them with cognitive abilities in order to allow ordinary users to program them easily and intuitively. One way of such programming is teaching work tasks by interactive demonstration. To make this effective and convenient for the user, the machine must be capable to establish a common focus of attention and be able to use and integrate spoken instructions, visual perceptions, and non-verbal clues like gestural commands. We report progress in building a hybrid architecture that combines statistical methods, neural networks, and finite state machines into an integrated system for instructing grasping tasks by man-machine interaction. The system combines the GRAVIS-robot for visual attention and gestural instruction with an intelligent interface for speech recognition and linguistic interpretation, and an modality fusion module to allow multi-modal task-oriented man-machine communication with respect to dextrous robot manipulation of objects.Comment: 7 pages, 8 figure