Autonomous driving paper index
AGNI: Adaptive Sensor Fusion and Terrain-Aware Navigation for Autonomous Ground Vehicles
One-line summary
This paper presents the mechanical design, sensor fusion strategy, path planning algorithms, and experimental validation of AGNI in challenging terrains.
Engineering notes
The robot employs a custom inverted V suspension system inspired by rocker-bogie designs for superior terrain adaptability.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
AGNI (Autonomous Ground-Based Navigation Inspector) is an autonomous ground vehicle designed for reliable operation in unstructured and GPS-denied environments. The robot employs a custom inverted V suspension system inspired by rocker-bogie designs for superior terrain adaptability. To achieve robust localization and navigation, AGNI integrates a Hybrid Confidence Adaptive Sensor Fusion (HCAF) mechanism that dynamically prioritizes sensor data based on real-time reliability scores. The system combines LiDAR, stereo vision camera, GPS-IMU (Used together for position estimation), and wheel encoders. Real-time obstacle avoidance is handled using the Dynamic Window Approach (DWA) along with Hybrid Confidence Adaptive Sensor Fusion and YOLO-based object detection. This paper presents the mechanical design, sensor fusion strategy, path planning algorithms, and experimental validation of AGNI in challenging terrains.
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