Ego Velocity

Ego-velocity estimation, the process of determining a system's own speed and direction, is crucial for autonomous navigation and robotics. Current research focuses on robustly estimating ego-velocity using diverse sensor modalities, including radar (employing techniques like phase-based approaches and acceleration-based constraint filters), event cameras (leveraging spiking neural networks and 3D Gaussian splatting), and even monocular vision (utilizing 3D convolutional neural networks with masked attention). These advancements improve accuracy and reliability, particularly in challenging conditions like low light or inclement weather, impacting fields like autonomous driving and mobile robotics.