Autonomous driving paper index
Autonomous Drone Navigation using Monocular Camera and Light Weight Embedded System
One-line summary
This paper proposes a method of achieving autonomous navigation using light weight embedded system and affordable monocular cameras by combining features of image processing and resource sharing.
Engineering notes
Key topics: autonomous driving, depth estimation, lidar, monocular camera, control. See the paper for implementation details and experimental results.
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
Autonomous robots are machines that can act without any human interference. When certain sensors and decision making algorithms are added to the control unit of a drone, the aerial vehicle is said to be autonomous. Such vehicles are capable of avoiding obstacles and correcting their local paths while staying on planned global paths. Autonomy in drones is usually achieved using many types of sensors like depth sensor, stereo camera or lidar, and intensive SLAM algorithms that require powerful processors. Though the existing methods work well, the scalability of such products is questionable as the economic and resource availability factors come into play. This paper proposes a method of achieving autonomous navigation using light weight embedded system and affordable monocular cameras by combining features of image processing and resource sharing. The proposed architecture makes use of monocular cues and midas depth estimation model to achieve obstacle avoidance and can run on any processor with basic features such as serial communication, wifi and camera ports.
Links and sources
Need this topic turned into a technical roadmap?
Full Self Driving can prepare a custom autonomous driving literature review, code map, dataset map, and B2B technology assessment.
Request B2B research
Comments