Projects and Grants

A list of our active projects and funding agencies including Joint Industry Projects (JIP). Scroll down for completed PhD Projects and Internship Projects.

Quick Links: [Kawada Robotics Corporation] [UoE-AIRS] [AvatarX] [EVA]

Current Projects & Grants

	Non-prehensile Manipulation with Admittance Control on Nextage Open robot      PI: Sethu Vijayakumar Grant Agency: Kawada Robotics Agency (UoE Research Explorer Page) Project Duration: January 2023 - August 2024
	PhD Studentship in Biomechanically Enabled Robot Support for Assisted Living        PI: Sethu Vijayakumar Grant Agency: Honda Research Institute Project Duration: September 2023 - August 2026
	The Microsoft Research - Royal Academy of Engineering Senior Research Fellowship in Robotics PI: Sethu Vijayakumar Grant Agency: RAEng and Microsoft (UoE Research Explorer Page) Project Duration: August 2017 - May 2027
	Institute Programme Director for Human-AI Interfaces and Robotics (Alan Turing Institute) PI: Sethu Vijayakumar Grant Agency: The Alan Turing Institute (UoE Research Explorer Page) Project Duration: September 2018 - August 2024
	HARMONY: Enhancing Healthcare with Assistive Robotic Mobile Manipulation (HARMONY) PI: Sethu Vijayakumar Grant Agency: Horizon 2020 (UoE Research Explorer Page) Project Duration: January 2021 - June 2024

Internship Projects

• [01] EVA (Elle Miller, 2022)

Completed PhD Projects (& Links to Thesis)

• [27] Concurrent Design and Motion Planning in Robotics using Differentiable Optimal Control (Traiko Dinev, 2023)
• [26] Robust SLAM and Motion Segmentation under Long-term Dynamic Large Occlusion (Ran Long, 2023)
• [25] Online Receding Horizon Planning of Multi-Contact Locomotion (Jiayi Wang, 2023)
• [24] Robustness to external disturbances for legged robots using dynamic trajectory optimisation (Henrique Ferrolho, 2022)
• [23] An Optimization-based Formalism for Shared Autonomy in Dynamic Environments (Christopher Mower, 2021)
• [22] Exoskeleton Assisted Locomotion(Daniel Gordon, 2021)
• [21] A Dyadic Collaborative Manipulation Formalism for Optimizing Human-Robot Teaming (Theodorous Stouraitis, 2021)
• [20] Controlling and Learning Constrained Motions for Manipulation in Contact (Joao Moura, 2021)
• [19] Experience-driven optimal motion synthesis in complex and shared environments(Wolfgang Merkt, 2020)
• [18] Dimensionality reduction for EMG prediction of upper-limb activity in freely-behaving primates (Agamemnon Krasoulis, 2017)

• [17] Motion synthesis for high degree-of-freedom robots in complex and changing environments (Yiming Yang, 2017) 

• [16] Exploiting variable impedance in domains with contacts (Andreea Radulescu, 2016)

• [15] Legged robotic locomotion with variable impedance joints (Alexander Enoch, 2015)

• [14] Novel approach for representing, generalising, and quantifying periodic gaits (Hsiu-Chin Lin, 2015)

• [13] Topology based representations for motion synthesis and planning (Vladimir Ivan, 2015)

• [12] Complex internal representations in sensorimotor decision making: a Bayesian investigation (Luigi Acerbi, 2015)

• [11] On probabilistic inference approaches to stochastic optimal control (Konrad Rawlik, 2013)

• [10] Closed-loop prosthetic hand : understanding sensorimotor and multisensory integration under uncertainty (Ian Saunders, 2012)

• [09] Information theoretic approach to tactile encoding and discrimination (Hannes Saal, 2011)

• [08] Nonlinear Dimensionality Reduction for Motion Synthesis and Control (Sebastian Bitzer, 2011)

• [07] Stochastic optimal control with learned dynamics models (Djordje Mitrovic, 2011)

• [06] Bayesian locally weighted online learning (Narayanan Edakunni, 2010)

• [05] Learning Control Policies from Constrained Motion (Matthew Howard, 2009)

• [04] Computational models of motor adaptation under multiple classes of sensorimotor disturbance (Adrian Haith, 2009)

• [03] Bayesian Multisensory Perception (Tim Hospedales, 2008)

• [02] Learning Dynamics for Robot Control under Varying Contexts (Georgios Petkos, 2008)

• [01] Probabilistic approaches to matching and modelling shapes (Graham McNeill, 2008)