视觉与机器人

自动驾驶

自动驾驶感知、规划、BEV、占用预测、激光雷达和仿真评测。

2026-03-06 至 2026-03-06 共收录 4 篇信号源：cs.RO, cs.CV, eess.IV, cs.AI

1. BEV与占用 4 篇

2603.01007 2026-03-06 cs.CV 89%

Dr.Occ: Depth- and Region-Guided 3D Occupancy from Surround-View Cameras for Autonomous Driving

Dr.Occ: 从环绕视图摄像头获取3D占用的深度和区域引导方法用于自动驾驶

Xubo Zhu, Haoyang Zhang, Fei He, Rui Wu, Yanhu Shan, Wen Yang, Huai Yu

机构 * School of Electronic Information, Wuhan University（武汉大学电子信息学院）； Horizon Robotics ； Wuhan University Shenzhen Research Institute（武汉大学深圳研究院）

专题命中 BEV与占用：autonomous driving(title,abstract)；occupancy(title,abstract)；driving perception(abstract)；分类 cs.CV

AI总结 Dr.Occ通过深度和区域引导方法提升自动驾驶中3D占用预测的几何对齐和语义学习效果。

Comments 10 pages, 6 figures. Accepted at CVPR 2026

2504.13596 2026-03-06 cs.CV cs.RO 84%

Collaborative Learning of Local 3D Occupancy Prediction and Versatile Global Occupancy Mapping

局部3D占用预测与多功能全局占用映射的协同学习

Shanshuai Yuan, Julong Wei, Muer Tie, Xiangyun Ren, Zhongxue Gan, Wenchao Ding

机构 * College of Intelligent Robotics and Advanced Manufacturing, Fudan University（智能机器人与先进制造学院，复旦大学）； State Key Laboratory of Intelligent Vehicle Safety Technology, Chongqing Changan Automobile Co., Ltd.（智能车辆安全技术重点实验室，重庆长安汽车有限公司）

专题命中 BEV与占用：occupancy(title,abstract)；autonomous driving(abstract)；分类 cs.RO、cs.CV

AI总结本文提出LMPOcc框架，通过整合全局占用先验提升局部预测性能，并实现全局地图的持续更新，适用于自动驾驶中的3D语义占用预测与大规模地图构建。

Comments Accepted by ICRA 2026

2505.06515 2026-03-06 cs.CV 83%

RESAR-BEV: An Explainable Progressive Residual Autoregressive Approach for Camera-Radar Fusion in BEV Segmentation

RESAR-BEV：一种可解释的逐步残差自回归方法用于摄像头-雷达融合的鸟瞰图分割

Zhiwen Zeng, Yunfei Yin, Zheng Yuan, Argho Dey, Xianjian Bao

机构 * College of Computer Science, Chongqing University（重庆大学计算机学院）； Department of Computer Science, Maharishi University of Management（Maharishi大学管理学院计算机系）

专题命中 BEV与占用：BEV(title,abstract)；autonomous driving(abstract)；分类 cs.CV

AI总结 RESAR-BEV通过残差自回归学习和双路径特征编码，实现摄像头-雷达融合的鸟瞰图分割，取得7类驾驶场景54.0% mIoU的最优性能并保持实时处理能力。

Comments This work was submitted to IEEE Transactions on Intelligent Transportation Systems (T-ITS) on 09-May-2025; revised 5 October 2025 and 26 January 2026; accepted 1 March 2026

2603.04643 2026-03-06 cs.HC 50%

Gamified Informed Decision-Making for Performance-Aware Design by Non-Experts: An Exoskeleton Design Case Study

游戏化辅助非专家进行性能感知设计：一个外骨骼设计案例研究

Arman Khalilbeigi Khameneh, Armin Mostafavi, Alicia Nahmad Vazquez

专题命中 BEV与占用：occupancy(abstract)

AI总结本文提出了一种游戏化决策框架，帮助非专家通过实时反馈优化外骨骼设计，提升设计效率和决策质量。

Comments https://www.ingentaconnect.com/content/iass/piass/2025/00002025/00000012/art00011

Journal ref International Association for Shell and Spatial Structures (IASS) 2025