3 accepted papers
Significant advances in robotics and machine learning have resulted in many datasets designed to support research into autonomous vehicle technology. However, these datasets are rarely suitable for a wide variety of navigation tasks. For example, datasets that include multiple cameras often have sho…
Motion estimation approaches typically employ sensor fusion techniques, such as the Kalman Filter, to handle individual sensor failures. More recently, deep learning-based fusion approaches have been proposed, increasing the performance and requiring less model-specific implementations. However, cur…
Visual Odometry (VO) is used in many applications including robotics and autonomous systems. However, traditional approaches based on feature matching are computationally expensive and do not directly address failure cases, instead relying on heuristic methods to detect failure. In this work, we pro…