Latest Articles for Robotics

A system generates lifelike hand interactions with various objects.

A quick method to create 3D models from just six photos, ideal for vehicles.

A new approach to improve multi-object tracking via 3D data.

New approach improves robot object manipulation by measuring energy margins for robustness.

Learn how breaking down complex tasks helps robots navigate effectively.

New framework GEASD enhances exploration in sparse reward settings.

A fresh approach to multi-robot coordination in rescue operations during emergencies.

New algorithms improve decision-making in constrained environments.

Exploring how sound field reconstruction impacts audio experiences across various applications.

A method to simplify complex multi-agent pathfinding challenges by breaking them into smaller parts.

Teaching robots tasks through simple demonstrations shows great potential for adaptability.

Exploring how robots can support children's growth and learning.

A new method combines traditional techniques with neural networks for better sound localization.

PIPER enhances reinforcement learning using preference-based feedback to tackle sparse rewards.

This article presents a method to control the shape of flexible objects using offline RL.

New methods improve how robots map their environment for specific tasks.

New tactile sensors improve how robots interact with objects.

New method improves robots' ability to grasp objects effectively and securely.

This study explores how robots learn walking through experience and symmetry.

A new method enhances teamwork among robots in complex environments.

A method for creating adaptable controllers for different robot designs.

Machine learning tackles decision-making with limited information using innovative methods.

Exploring strategies for optimizing energy levels and rewards in Markov Decision Processes.

Exploring the dynamics and applications of self-aligning active systems.

A new framework improves self-driving car behavior through advanced learning techniques.

Methods for robots to locate fast-moving targets with limited information.

A new framework helps robots learn individual preferences for household tasks.

A look at how hybrid feedback helps robots avoid obstacles.

A study on enhancing mobile robot location recognition using advanced neural networks.

New method enhances agent decision-making in complex environments.

Robotic systems are shaping the future of neurosurgery, improving safety and precision.

Research on optimizing UAV laser targeting and motion planning.

This study presents methods for oscillator synchronization despite faults and malicious behavior.

This article discusses the significance and techniques of recognizing objects in 3D using multiple views.

A new approach reduces coordination in multi-agent systems for better navigation.

Enhancing control strategies for systems while avoiding obstacles.

A look into how machines learn from past data without real-time interaction.

Efficient methods for assigning tasks to multiple robots in real-time environments.

A clear look at how shapes change and adapt in various contexts.

MA-COPP offers new insights into predicting outcomes in complex multi-agent settings.