Latest Articles for Autonomous Systems

A look into safe learning with multiple agents in constrained environments.

QNNRepair improves the accuracy of neural networks after quantization.

A new method improves evaluation of dense maps from LiDAR data.

Robots efficiently create shapes using color codes and specific movement strategies.

Examining risk analysis methods for safe self-driving technology.

A new system enhances off-road vehicle terrain assessment using LiDAR and camera data.

Exploring the role of kernel methods in improving reinforcement learning methods.

A new method enhances object detection adaptability to diverse data.

New methods ensure robots safely cover areas while adapting to challenges.

This article examines how to assess the intentions of AI systems.

A new method improves learning from uneven datasets in offline reinforcement learning.

New safety shields address delays in autonomous systems to ensure safer operation.

SEPT improves wireless transmission of 3D point clouds using deep learning.

A new method enhances image transmission through efficient two-way communication.

A new metric improves model prediction accuracy and clarity.

Research introduces efficient models for predicting ship orientation using deep learning techniques.

A new framework enhances safety and efficiency in urban air transport.

A new method enhances efficiency in robot motion planning and collision detection.

Introducing a method to enhance reliability in image retrieval for critical applications.

A novel framework to strengthen reinforcement learning models in unpredictable environments.

New modulation techniques improve wireless communication in high-speed scenarios and environments.

AI enhances satellite data processing for quicker, intelligent decision-making in space.

New framework improves underwater mapping and sensing despite environmental challenges.

GP-Frontier allows robots to navigate without maps by using real-time sensing.

A new method enables drones to track each other using cameras and IMUs.

OMIGA enhances offline multi-agent learning by integrating global and local learning strategies.

Research focuses on improving information processing in safety-critical autonomous systems.

A new approach enhances safety in reinforcement learning tasks without prior rewards.

QUAM enhances uncertainty estimates in predictions across various fields.

This article explores how drones use reinforcement learning for safe navigation in forests.

A new method enhances low-light images while reducing noise and preserving colors.

A look at NS-POMDPs and their impact on decision-making in uncertain environments.

This paper introduces responsibility anticipation for better decision-making in multi-agent interactions.

Autonomous vehicles enhance parking space estimation for better congestion management.

A new method improves Bayesian neural networks for generalization and uncertainty estimation.

Exploring how robots enhance environmental data collection through autonomous decision-making.

Discover advancements in decentralized Q-learning for multi-agent systems.

The 2nd BARN Challenge showcased advancements in autonomous robot navigation systems.

GP-MPPI combines real-time sensing and path planning for robotic navigation.

Explore how nonlinear meta-learning improves task learning efficiency and accuracy.