ABSTRACT: To address the limitations of traditional multi-camera-IMU state estimation systems—namely, insufficient localization accuracy in complex environments and poor robustness under abnormal IMU ...

In this tutorial, we present an advanced, hands-on tutorial that demonstrates how we use Qrisp to build and execute non-trivial quantum algorithms. We walk through core Qrisp abstractions for quantum ...

Simultaneous localization and mapping (SLAM) is widely used in autonomous driving, augmented reality, and embodied intelligence. In real-world settings, sensor measurements often suffer from ...

Do you remember the early days of social media? The promise of connection, of democratic empowerment, of barriers crumbling and gates opening? In those heady days, the co-founder of Twitter said that ...

Abstract: In dynamic environments, dynamic objects pose significant challenges to visual Simultaneous Localization and Mapping (SLAM) algorithms. They can lead to positioning drift, degradation of the ...

(Reuters) - A conservative U.S. appeals court judge took the unusual step on Thursday of recording himself handling several handguns and explaining their mechanisms to explain why his colleagues had ...

This project is a hands-on implementation to explore and understand the concepts behind Simultaneous Localization and Mapping (SLAM). It uses a simulated laser sensor to detect obstacles and create a ...

ROS-based multi-agent system for path planning and LiDAR SLAM mapping in dynamic environments. This project is a hands-on implementation to explore and understand the concepts behind Simultaneous ...

Abstract: Simultaneous Localization and Mapping (SLAM) algorithms with multiple autonomous robots have received considerable attention in recent years. In general, SLAM algorithms use odometry ...