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Found 11 papers, 5 papers with code
Out of the Room: Generalizing Event-Based Dynamic Motion Segmentation for Complex Scenes
Rapid and reliable identification of dynamic scene parts, also known as motion segmentation, is a key challenge for mobile sensors.
U-BEV: Height-aware Bird's-Eye-View Segmentation and Neural Map-based Relocalization
Efficient relocalization is essential for intelligent vehicles when GPS reception is insufficient or sensor-based localization fails.
SCIM: Simultaneous Clustering, Inference, and Mapping for Open-World Semantic Scene Understanding
In order to operate in human environments, a robot's semantic perception has to overcome open-world challenges such as novel objects and domain gaps.
Self-Improving Semantic Perception for Indoor Localisation
We find memory replay an effective measure to reduce forgetting and show how the robotic system can improve even when switching between different environments.
A Fully-Integrated Sensing and Control System for High-Accuracy Mobile Robotic Building Construction
We present a fully-integrated sensing and control system which enables mobile manipulator robots to execute building tasks with millimeter-scale accuracy on building construction sites.
Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes
Foreground objects are therefore detected as areas in an image for which the descriptors are unlikely given the background distribution.
3D Multi-Robot Patrolling with a Two-Level Coordination Strategy
This target selection relies on a shared idleness representation and a coordination mechanism preventing topological conflicts.
AMZ Driverless: The Full Autonomous Racing System
This paper presents the algorithms and system architecture of an autonomous racecar.
Robotics
Redundant Perception and State Estimation for Reliable Autonomous Racing
In autonomous racing, vehicles operate close to the limits of handling and a sensor failure can have critical consequences.
Modular Sensor Fusion for Semantic Segmentation
Sensor fusion is a fundamental process in robotic systems as it extends the perceptual range and increases robustness in real-world operations.
X-View: Graph-Based Semantic Multi-View Localization
Our findings show that X-View is able to globally localize aerial-to-ground, and ground-to-ground robot data of drastically different view-points.
