Challenges in Visual Anomaly Detection for Mobile Robots
We consider the task of detecting anomalies for autonomous mobile robots based on vision. We categorize relevant types of visual anomalies and discuss how they can be detected by unsupervised deep learning methods. We propose a novel dataset built specifically for this task, on which we test a state-of-the-art approach; we finally discuss deployment in a real scenario.
Code (1)
Tasks
Anomaly DetectionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
An Outlier Exposure Approach to Improve Visual Anomaly Detection Performance for Mobile Robots
We consider the problem of building visual anomaly detection systems for mobile robots. Standard anomaly detection models are trained using large datasets composed only of non-anomalous data. However, in robotics applica…
Anomaly DetectionDynamic Fusion Module Evolves Drivable Area and Road Anomaly Detection: A Benchmark and Algorithms
Joint detection of drivable areas and road anomalies is very important for mobile robots. Recently, many semantic segmentation approaches based on convolutional neural networks (CNNs) have been proposed for pixel-wise dr…
Anomaly DetectionSelf-Driving CarsSemantic SegmentationDeep Visual Odometry Methods for Mobile Robots
Technology has made navigation in 3D real time possible and this has made possible what seemed impossible. This paper explores the aspect of deep visual odometry methods for mobile robots. Visual odometry has been instru…
Simultaneous Localization and MappingVisual OdometryMultimodal Anomaly Detection based on Deep Auto-Encoder for Object Slip Perception of Mobile Manipulation Robots
Object slip perception is essential for mobile manipulation robots to perform manipulation tasks reliably in the dynamic real-world. Traditional approaches to robot arms' slip perception use tactile or vision sensors. Ho…
Anomaly DetectionObjectApplying Surface Normal Information in Drivable Area and Road Anomaly Detection for Ground Mobile Robots
The joint detection of drivable areas and road anomalies is a crucial task for ground mobile robots. In recent years, many impressive semantic segmentation networks, which can be used for pixel-level drivable area and ro…
Anomaly DetectionSegmentationSemantic Segmentation