Heriot-Watt University

Transparent Multimodal Interaction For Domestic Robots

Project number: 
600001
The goal is to further research and development for domestic robots, interacting with people in the home.
Prof. Helen Hastie
Heriot-Watt University

Dyson is a leading global consumer product company, with its UK campus based near Bristol. Dyson is currently investing heavily in Robotics and this project would be industrially supervised within Dyson’s Robotics Research group.

Mobile Robotic Manipulator System for Large Structure Manufacturing

Project number: 
140031
To realize the control of a mobile manipulator robotic system, composed of a mobile base and an attached robotic arm, for optimal position precision; simultaneous control of a mobile base and robot arm to supress disturbances; to develop closed loop visuo-control techniques for maximum precision. <img src="/sites/default/files/styles/medium/public/huskysuphi.jpg?itok=A7KM2pQq" width="220" height="146" alt="" class="image-medium" />
Dr. Mustafa Suphi Erden
Heriot-Watt University

Robotic Surgery Training System – Robot Control, System Design

Project number: 
120023
To realize the control of robots in a Robotic Surgery Training System to emulate the actual movements and capability of robot manipulators in an actual robotic surgical system, to design and design and develop semi-automated robotic procedures to assist Robotic surgery procedures, to develop and evaluate user control units to operate the Robotic Surgery Training System.
Dr. Mustafa Suphi Erden
Heriot-Watt University

University: 
Heriot-Watt University

Autonomous Digital twinning at the Edge

Project number: 
123407
Framework and methods for autonomous creation of digital twins
Dr. Theo Lim
Heriot-Watt University

Digital twins are increasingly becoming a choice, if not a trend to forecast, operate and manage complex systems. However, all digital twins are derived from human defined models about the environment or the physical asset.  That is, the human defines the digital proxies, the virtualised environment, the technology, etc.  This project questions the potential of machines and/or networks to derive its own digital model and workspace. In particular, the emphasis on systems that are beyond human visual sight and where communication synchronicity is not guaranteed, i.e.

Spatial Modelling to support Contextually Aware User Interfaces

Project number: 
124026
Develop novel spatial modelling algorithms and implementations on the edge for real-time context understand for robots including autonomous vehicles
Dr. Phil J. Bartie
Heriot-Watt University

Human-robot interaction requires building a joint understanding of context, facilitating collaboration naturally and seamlessly on tasks, e.g. by joint goal setting, communicating progress or clarifying the user’s intention. To achieve the ability of natural command, control, and feedback in real world scenarios requires the construction of user interaction models supported by spatial modelling and reasoning, that can link a detailed digital landscape to real world concepts. 

Socially Assistive Robot Support to aid recovery after critical illness

Project number: 
200027
This project aims to use case studies and technical robot pilots to evaluate the feasibility and acceptability of using SARs for patients recovering after critical care.
Prof. Lynne Baillie
Heriot-Watt University

Critical illness can affect individuals at any age and for a wide range of medical and surgical conditions. Recovery can be prolonged, and complicated by fatigue, impaired attention and limited engagement with rehabilitation for physical and mental health reasons. Socially assistive robots provide an opportunity for bespoke rehabilitation programmes to be developed by health care professionals, then delivered by the robot, from the time of recovery from critical care, through the rest of the inpatient journey, to the transition home.

Interactive Question Answering and Content Delivery

Project number: 
240020
Develop deep learning models that generate responses to open-domain questions grounded on Knowledge Bases, Common sense reasoning and text sources (e.g., News articles) via conversation. Challenges include dataset collection and building scalable ML models.
Dr. Ioannis Konstas
Heriot-Watt University

Interactions with current AI agents (e.g.,  Amazon Alexa, Google Home,  Apple Siri) are limited to single-turn simple tasks such as asking about the weather, listening to a song, or telling a joke. What they are currently lacking is a more in-depth multi-turn conversation on wider domains (e.g., talking about the news) that entail follow-up questions, retrieving information from knowledge bases (e.g., WikiData), texts (e.g., news articles) and performing common-sense reasoning (e.g., if-then clauses). 

Neurorobotics Approach to Learn On the Fly

Project number: 
120022
To evolve robot controllers that are capable of online learning and thus more suitable to critical robotics applications that involve processing of big data
Dr. Patricia A. Vargas
Heriot-Watt University

In this project, we will explore a Neurorobotics approach to develop robotic controllers to scenarios which behavioural responses must be fast and precise whilst limited to strict energy constraints. This will be accomplished by the use of Evolving Spiking Neural Networks (ESNN) models.

Results from this project would be applicable to robotics in search and rescue missions, dangerous scenarios, critical operations and a plethora of human-robot-interaction scenarios, where enhanced autonomy, robustness and rapid responses are of vital importance.