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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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51#
發(fā)表于 2025-3-30 09:46:43 | 只看該作者
52#
發(fā)表于 2025-3-30 15:13:28 | 只看該作者
Trajectory Planning of Mobile Robot for Obstacle Avoidance Considering Time and Path Lengthroduced. By expressing the cost function in terms of the time at which the robot avoids moving obstacles, the trajectory planning is formulated as an optimization problem. To verify the effectiveness of considering both time and path length, several simulations and experiments are carried out.
53#
發(fā)表于 2025-3-30 19:27:50 | 只看該作者
Conference proceedings 2024usehold domains. These advancements in technology and application domains have brought forth the need for continuous research and development to address new challenges in deploying intelligent autonomous systems in a reliable and user-independent manner..?This book is a compilation that aims to serv
54#
發(fā)表于 2025-3-30 22:13:30 | 只看該作者
Revisiting the Minimum Constraint Removal Problem in Mobile Roboticshe plane, instances of the minimum constraint removal problem with minimum removable obstacles lower than . can be solved in polynomial time. This result is also empirically validated using several instances of randomly sampled axis-parallel rectangles.
55#
發(fā)表于 2025-3-31 03:13:21 | 只看該作者
RCBEVD: Radar-Camera Fusion in Bird’s Eye View for Detection with Velocity Estimationies are fused with 2D object detection bounding boxes to give BEV detections. RCBEVD is evaluated on the nuScenes dataset benchmark using the Average Velocity Error (AVE) and Average Precision (AP) metrics. We outperform the baseline method CenterFusion’s Mean Average Velocity Error (mAVE) ., an improvement of . on the nuScenes validation dataset.
56#
發(fā)表于 2025-3-31 06:51:59 | 只看該作者
57#
發(fā)表于 2025-3-31 12:13:59 | 只看該作者
58#
發(fā)表于 2025-3-31 15:46:53 | 只看該作者
59#
發(fā)表于 2025-3-31 17:41:29 | 只看該作者
Holistic Assembly Planning Framework for Dynamic Human-Robot Collaborationresource capability, part dependencies, timing, and adaptability to human behavior. An expert is kept in the loop to enrich the data and to review and modify the automatically generated sequences. Preliminary results show assembly sequence plans for human-robot collaboration (HRC) as an output with less cycle times compared to human-only assembly.
60#
發(fā)表于 2025-3-31 23:53:39 | 只看該作者
Improvement of Position Error Rate of Docking of Autonomous Mobile Robot with Object Recognition andtrasonic sensor and the object recognition data, and the resulting position error rate is compared. Through this experiment, we confirmed the improvement of the position error rate of the two experiments.
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