Autonomous systems possess the features of inferring their own state, understanding their
surroundings, and performing autonomous navigation. With the applications of learning …

Compared to the onboard camera and laser scanner, radar sensor provides lighting and
weather invariant sensing, which is naturally suitable for long-term localization under …

Unmanned aerial vehicles (UAVs) are becoming popular nowadays due to their versatility
and flexibility for indoor applications, such as the autonomous visual inspection of the inner …

Object SLAM is a popular approach for autonomous driving and robotics, but accurate object
perception in outdoor environments remains a challenge. State-of-the-art object SLAM …

Visual localization estimation is highly depended on the quality of video frames or captured
images. Estimation quality may be affected by the poor visibility, low background texture and …

In the application of intelligent mobile robots, the odometry is the key system for
implementing positioning. Traditional feature extraction algorithms can not work stably in …

Accurately perceiving location and scene is crucial for autonomous driving and mobile
robots. Recent advances in deep learning have made it possible to learn egomotion and …

Unreliable feature extraction and matching in handcrafted features undermine the
performance of visual SLAM in complex real-world scenarios. While learned local features …

Robust positioning is a central issue in robots. Due to the complex indoor environment,
visual simultaneous localization and mapping (VSLAM) is susceptible to light and some …

视觉里程计是SLAM (Simultaneous Localization and Mapping) 领域中的基石,
单目视觉里程计因其成本低廉和仅需较少的相机标定工作而占据着重要的地位 …