The growing demand for robots able to act autonomously in complex scenarios has widely
accelerated the introduction of Reinforcement Learning (RL) in robots control applications …

A critical aspect of evolution is the layer of developmental physiology that operates between
the genotype and the anatomical phenotype. While much work has addressed the evolution …

Legged robotic technologies have moved out of the lab to operate in real environments,
characterized by a wide variety of unpredictable irregularities and disturbances, all this in …

In traditional robotics, model-based controllers are usually needed in order to bring a robotic
plant to the next desired state, but they present critical issues when the dimensionality of the …

Evolution gave humans advanced grasping capabilities combining an adaptive hand with
efficient control. Grasping motions can quickly be adapted if the object moves or deforms …

Advances in legged robotics are strongly rooted in animal observations. A clear illustration
of this claim is the generalization of Central Pattern Generators (CPG), first identified in the …

The increasing number of robots and the rising cost of electricity have spurred research into
energy-reducing concepts in robotics. One such concept, elastic actuation, introduces …

How well simulation results can be transferred to the real world depends to a large extent on
the sim-to-real gap that therefore should be as small as possible. In this work, this gap is …

Reinforcement learning (RL) methods play a crucial role in training bipedal robot
locomotion. However, there exists a practical challenge in that well-trained robot policies …

Reinforcement learning (RL) offers the chance to make a system learn control policies to
successfully and autonomously perform specific tasks. It is often applied to classical and …