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Titlebook: Intelligent Autonomous Systems 18; Volume 1 Proceedings Soon-Geul Lee,Jinung An,Joo H. Kim Conference proceedings 2024 The Editor(s) (if ap

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11#
發(fā)表于 2025-3-23 10:13:10 | 只看該作者
Global Map Generation Using Local Feature Grid Maps for Autonomous Vehicles in Frequently Changing Oon algorithms are prone to frequent environmental changes such as light and reflections or foliage, dust, and vegetation. Humans, however, can navigate in such environments, mainly when they drive the same route frequently. They remember their environment and rely on their stored knowledge. State-of
12#
發(fā)表于 2025-3-23 17:36:27 | 只看該作者
13#
發(fā)表于 2025-3-23 18:17:35 | 只看該作者
RCBEVD: Radar-Camera Fusion in Bird’s Eye View for Detection with Velocity Estimationness. The outputs from these sensors are often fused to generate more accurate perception results, due to their complementary features. In this paper, we propose a method, RCBEVD: Radar-camera fusion in Bird’s Eye View (BEV) representation for detection with velocity estimation. We introduce a novel
14#
發(fā)表于 2025-3-23 22:19:17 | 只看該作者
15#
發(fā)表于 2025-3-24 05:58:39 | 只看該作者
Automatic Lane Change Using Adaptive Grid Map and make driving more convenient for the driver. In this paper, adaptive grid and occupancy map methods are proposed for automatic lane change. Nine grids are formed based on the ego vehicle to create an active occupancy grid map on the lane change request of the driver. It is suitable for use in a
16#
發(fā)表于 2025-3-24 08:25:02 | 只看該作者
17#
發(fā)表于 2025-3-24 11:24:00 | 只看該作者
Factor Graph-Based Dense Mapping for Mobile Robot Teams Using VDB-Submapsdered solved for years, there still exist various environments, use cases, or robot configurations which require new approaches in order to successfully perform the task. This work addresses how a group of mobile robots can collaboratively create a . 3D map that is globally consistent and accounts f
18#
發(fā)表于 2025-3-24 16:20:16 | 只看該作者
19#
發(fā)表于 2025-3-24 20:22:28 | 只看該作者
Improvement of Position Error Rate of Docking of Autonomous Mobile Robot with Object Recognition anda. In an autonomous mobile robot, the angle is calculated using only ultrasonic data, and the resulting position error rate is docked by fusing the ultrasonic sensor and the object recognition data, and the resulting position error rate is compared. Through this experiment, we confirmed the improvem
20#
發(fā)表于 2025-3-24 23:14:11 | 只看該作者
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