Teachers’ Perspective on Fostering Computational Thinking Through Educational Robotics

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Identifying important sensory feedback for learning locomotion skills

Auke Ijspeert, Guillaume Denis Antoine Bellegarda, Milad Shafiee Ashtiani

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 ...

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Smell Driven Navigation for Soft Robotic Arms: Artificial Nose and Control

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Elephants and other animals heavily rely on the sense of smell to operate. Soft robots would also benefit from an artificial sense of smell, which could be helpful in typical soft robotic tasks such as search and rescue, pipe inspection, and all the tasks ...

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

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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 ...

2023

Self-Correcting Quadratic Programming-Based Robot Control

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Quadratic Programming (QP)-based controllers allow many robotic systems, such as humanoids, to successfully undertake complex motions and interactions. However, these approaches rely heavily on adequately capturing the underlying model of the environment a ...

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Human-Robot Swarm Interaction: An Explorative Path to Foster Complex Systems Understanding

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Order, regularities, and patterns are ubiquitous around us. A flock of birds maneuvering in the sky, the self-organization of social insects, a global pandemic or a traffic jam are examples of complex systems where the macroscopic patterns arise from the m ...

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Implicit Distance Functions: Learning and Applications in Robotics

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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 ...

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Computational Models of Mutual Understanding for Human-Robot Collaborative Learning

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There is a growing trend towards designing learning activities featuring robots as collaborative exercises where children work together to achieve the activity objectives, generating interactions that can trigger learning processes. Witnessing such activit ...

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Morphological flexibility in robotic systems through physical polygon meshing

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Shape-changing robots adapt their own morphology to address a wider range of functions or environments than is possible with a fixed or rigid structure. Akin to biological organisms, the ability to alter shape or configuration emerges from the underlying m ...

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Sensorless force and displacement estimation in soft actuators

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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 ...

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Digital Intervention for Collaborative and Human-Centered Activities in Design-Based Learning Scenarios

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Training science and engineering students to become responsible citizens and professionals requires novel and creative pedagogical approaches, such as design thinking. This concept relies on processes and tools to develop creativity and problem-solving ski ...

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