Designing Tools and Activities for Educational Robotics in Online Learning

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Model-based reinforcement learning for robot control offers the advantages of overcoming concerns on data collection and iterative processes for policy improvement in model-free methods. However, both methods use exploration strategy relying on heuristics ...

Sensing forms an integral part of soft matter based robots due to their compliance, dependence on loading conditions, and virtually infinite degrees of freedom. Previous studies have developed several extrinsic sensors and embedded them into soft actuators ...

In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...

Soft robot are celebrated for their propensity to enable compliant and complex robot-environment interactions. Soft robotic manipulators, or slender continuum structure robots have the potential to exploit these interactions to enable new exploration and m ...

Robot motor skills can be acquired by deep reinforcement learning as neural networks to reflect state-action mapping. The selection of states has been demonstrated to be crucial for successful robot motor learning. However, because of the complexity of neu ...

The following data contain the information and files, which are required to recreate and build the experimental setup that is described in the Laboratory manual. Further details can be found in the associated publication “A graduate laboratory experiment t ...

Computers have long been augmenting human capabilities and communication, and with emerging technologies, physical immersion in virtual worlds is now attainable. These advancements push the boundaries of human potential, allowing designers, architects, eng ...

Many countries struggle to effectively introduce Digital Education (DE) to all K-12 students as they lack adequately trained teachers. While cascade models of in-service teacher-professional development (PD) can rapidly deploy PD-programs through multiple ...

Robotic surgery is a promising direction to improve surgeons and assistants’ daily life with respect to conventional surgery. In this work, we propose solo laparoscopic surgery in which two robotic arms, controlled via haptic foot interfaces, assist the ta ...

Empirical evidence shows that memories that are frequently revisited are easy to recall, and that familiar items involve larger hippocampal representations than less familiar ones. In line with these observations, here we develop a modelling approach to pr ...

Professional skills of project planning, risk analysis, ethical design, communication, and working in interprofessional teams are now recognised as core engineering skills. Frequently, they are addressed in engineering education through team projects. Howe ...

Designing Tools and Activities for Educational Robotics in Online Learning

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Exploration-based model learning with self-attention for risk-sensitive robot control

Sensorless force and displacement estimation in soft actuators

Implicit Distance Functions: Learning and Applications in Robotics

Piecewise Affine Curvature model: a reduced-order model for soft robot-environment interaction beyond PCC

Identifying important sensory feedback for learning locomotion skills

Acoustic Levitation apparatus (Robotics Practicals)

Human Interactive Robotic Surfaces for Physical Immersion

An adapted cascade model to scale primary school digital education curricular reforms and teacher professional development programs

Enabling four-arm laparoscopic surgery by controlling two robotic assistants via haptic foot interfaces

A dynamic attractor network model of memory formation, reinforcement and forgetting

The development, validation and use of an interprofessional project management questionnaire in engineering education