Stipend and Home Fees

Exploiting Novel Representations for Constrained Multi-Robot Collaborative Loco Manipulation

Project number: 
123022
The principle goal of the project is to address multi-robot loco-manipulation tasks; both from a decentralised planning as well as predictive control perspective. The aim is to realise human-robot teaming for handling rigid and/or actuated object.
Prof. Sethu Vijayakumar FRSE
University of Edinburgh

The aim of this project is to enable a team of mobile manipulators with the capability of dexterous simultaneous manipulation and locomotion.

Game Theoretic Approaches to Advancing Physical Human-Robot Collaborations through Nudging

Project number: 
120025
Create a robotic system that can infer and influence human behaviour to assist humans in physical collaborative tasks. Develop a game theoretic framework to improve human-robot physical collaboration using implicit communication processes, such as intent estimation and nudging as well as explicit feedforward sensory cues. Embed this into an existing methodology of optimal control (OC) based hybrid trajectory optimisation (TO) for realising dyadic collaborative tasks using existing co-bot setup.
Prof. Sethu Vijayakumar FRSE
University of Edinburgh

Humans perform numerous tasks in their daily life that require collaboration with others. In these scenarios the two humans work together, anticipate how the other will behave and guide their partner towards the joint goal. For instance, two humans can effortlessly move and flip large boxes in a warehouse. Likewise, a human can pour wine into a glass held out by another human, without spilling.

Radio Frequency Simultaneous Localisation and Mapping (RF SLAM) for Robot Navigation

Project number: 
100021
To develop autonomous navigation system based on ubiquitous RF signals
Prof. Tughrul Arslan
University of Edinburgh

Robots and UAVs are often required to operate (semi)autonomously, especially when there is limited human awareness for safe operation. In such cases, self-navigation functionalities are required. This proposal relates to the adaptation of RF signals of opportunity for navigation using SLAM approaches.

Multi-Agent Reinforcement Learning

Project number: 
300009
Develop and evaluate algorithms for multi-agent reinforcement learning in complex environments
Dr. Stefano Albrecht
University of Edinburgh

Multi-agent reinforcement learning (MARL) uses reinforcement learning techniques to train a set of agents to solve a specified task. This includes agents working in a team to collaboratively accomplish tasks, as well as agents in competitive scenarios with conflicting interests. Recent advances in MARL have leveraged deep learning to scale to bigger problems and address some of the inherent challenges in MARL [1].

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

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.