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Brain-inspired navigation and sensing for robots

Published in Frontiers in Neurorobotics

Prioritized experience replay in path planning via multi-dimensional transition priority fusion

Published in Frontiers in Neurorobotics

Introduction Deep deterministic policy gradient (DDPG)-based path planning algorithms for intelligent robots struggle to discern the value of experience transitions during training due to their reliance on a random experience replay. This can lead to inappropriate sampling of experience transitions and overemphasis on edge experience transitions. A...

Bio A.I. - from embodied cognition to enactive robotics

Published in Frontiers in Neurorobotics

Dense captioning and multidimensional evaluations for indoor robotic scenes

Published in Frontiers in Neurorobotics

The field of human-computer interaction is expanding, especially within the domain of intelligent technologies. Scene understanding, which entails the generation of advanced semantic descriptions from scene content, is crucial for effective interaction. Despite its importance, it remains a significant challenge. This study introduces RGBD2Cap, an i...

Exploring the EMG transient: the muscular activation sequences used as novel time-domain features for hand gestures clas...

Published in Frontiers in Neurorobotics

Introduction Muscular activation sequences have been shown to be suitable time-domain features for classification of motion gestures. However, their clinical application in myoelectric prosthesis control was never investigated so far. The aim of the paper is to evaluate the robustness of these features extracted from the EMG signal in transient sta...

Harmonizing minds and machines: survey on transformative power of machine learning in music

Published in Frontiers in Neurorobotics

This survey explores the symbiotic relationship between Machine Learning (ML) and music, focusing on the transformative role of Artificial Intelligence (AI) in the musical sphere. Beginning with a historical contextualization of the intertwined trajectories of music and technology, the paper discusses the progressive use of ML in music analysis and...

Cross-modal self-attention mechanism for controlling robot volleyball motion

Published in Frontiers in Neurorobotics

Introduction The emergence of cross-modal perception and deep learning technologies has had a profound impact on modern robotics. This study focuses on the application of these technologies in the field of robot control, specifically in the context of volleyball tasks. The primary objective is to achieve precise control of robots in volleyball task...

Peg-in-hole assembly skill imitation learning method based on ProMPs under task geometric representation

Published in Frontiers in Neurorobotics

Introduction Behavioral Cloning (BC) is a common imitation learning method which utilizes neural networks to approximate the demonstration action samples for task manipulation skill learning. However, in the real world, the demonstration trajectories from human are often sparse and imperfect, which makes it challenging to comprehensively learn dire...

Fuzzy super twisting mode control of a rigid-flexible robotic arm based on approximate inertial manifold dimensionality ...

Published in Frontiers in Neurorobotics

Introduction The control of infinite-dimensional rigid-flexible robotic arms presents significant challenges, with direct truncation of first-order modal models resulting in poor control quality and second-order models leading to complex hardware implementations. Methods To address these issues, we propose a fuzzy super twisting mode control method...

Learning geometric Jensen-Shannon divergence for tiny object detection in remote sensing images

Published in Frontiers in Neurorobotics

Tiny objects in remote sensing images only have a few pixels, and the detection difficulty is much higher than that of regular objects. General object detectors lack effective extraction of tiny object features, and are sensitive to the Intersection-over-Union (IoU) calculation and the threshold setting in the prediction stage. Therefore, it is par...