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Safe and reliable human-robot interaction

   Doctoral College

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  Dr Khizer Saeed, Dr Almas Baimagambetov  No more applications being accepted  Funded PhD Project (UK Students Only)

About the Project

The project will be undertaken at the recently funded multidisciplinary Robotics, Control and Artificial Intelligence (MOCAI) research laboratory. The concept of human-robot collaboration has wider application in many practical areas of global strategic sectors such as smart living, transportation, healthcare, digital manufacturing, monitoring and exploration and many more.

The recent surge of research interest in the human-robot interaction (HRI) has been devoted to the development of methodologies to achieve intelligent and safe human-robot interaction. The physical HRI is defined when human(s), robot(s) and the environment come into contact with each other and form a tightly coupled dynamic system to accomplish a task. Safe human-robot interaction demands the development of the new methodologies so that task-related information is communicated efficiently between human and robots. Current HRI works on sensors but this project will investigate using novel image-analysis techniques instead. The overall aim of the research project is to develop fast response methodologies for safer and reliable human-robot interactions and is reflected in the following key objectives: 

Objective 1: Developing human-robotic gesture mapping. The key to implementing the humanoid motion of a robotic arm using gestures is to fuse the motion features of the human arm into the robotic arm, which requires mapping the relationship between them. However, mapping of human-robotic arm is a highly challenging process because of the complexities in implementing the kinematics of extensions and rotations in shoulder complex, elbow complex and wrist joint. The objective, which is primarily a programming-driven task, will be to develop the methodologies for gestural information and segmentation using image-based gesture recognition of human hands, learning algorithms and skeleton models. The outcome will be a software tool capable of interfacing with a robotic arm. The tool will contain gesture libraries, algorithms for gesture identification and tracking which can be translated into robot commands to safely undertake predefined tasks. 

Objective 2: Developing the humanoid motion of a robot arm. This part of the project will develop the “RoboThespian” humanoid robot in the MOCAI research laboratory to provide 6 degrees of freedom (DOF). Using the software tool and the libraries developed during objective 1, a range of experiments will be undertaken to develop robotic arm movements by analyzing the difference between the robotic arm and human arm for the shoulder joint with 1 DOF, an elbow joint with 1DOF, and a wrist joint with 3 DOF, and 1DOF rotation of the arm about its shoulder base. This will require the development of the novel architecture for both hardware (robotic arm) and software (the software tool for gesture mapping) based on humanoid motion rules (HMR) and reinforcement learning (RL). The development of HMR rules will allow the robot arm to mimic the trajectory motion of a humanoid arm. The RL leaning will solve the complex and difficult motion control tasks of the robotic arm to implement humanoid tasks of the robotic arm. This will lead to the development of efficient humanoid motion planning of the robotic arm for a specific task.

Funding Notes

This studentship is funded by the University of Brighton and is open to applications from candidates considering a full time or part time mode of study. The studentship consists of full UK fees, a Doctoral Stipend at the UKRI rate and a research training support grant. FT study, the studentship is for 3 years, PT study for 6 years, with the stipend being 50% of the UKRI rate.
A part time route is not available to applicants who will need a student visa to study in the UK.
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