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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 ...
Autonomous robots have the potential to fundamentally transform conventional farming methods, e.g. by enabling economically viable farming of sloped arable land. However, navigation on slopes in harsh conditions is challenging for robots as they must be pr ...
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 ...
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 ...
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 ...
Humans coordinate the abundant degrees of freedom (DoFs) of hands to dexterously perform tasks in everyday life. We imitate human strategies to advance the dexterity of multi-DoF robotic hands. Specifically, we enable a robot hand to grasp multiple objects ...
Robotization and industrial automation are important fields of research and development in engineering. At micro scales, industrial automation development requires specific tools to handle components and perform precise assembly, etc. Therefore, the develo ...
Robotic technologies have shown the capability to interact with living organisms and even to form integrated mixed societies composed of living and artificial agents. Biocompatible robots, incorporating sensing and actuation capable of generating and respo ...
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 ...
As the field of ethology advances, especially over the past two decades, the role of animal-robot interaction tools has increasingly become essential. This importance arises from the need for controlled, repetitive, repeatable, and long-duration experiment ...