Self Driving Robot using Neural Network

Engineering notes

Key topics: self-driving vehicle, self-driving, autonomous vehicle, prediction, 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

Nowadays development of autonomous vehicles gained a lot of interest of most of researchers. Autonomous vehicle has ability to sense surrounding environment and navigate without any human intervention. The potential benefits of autonomous vehicle include reduction in infrastructure cost, increased safety with significant reduction in traffic collisions. This paper introduces the autonomous robot which is a scaled down version of actual self-driving vehicle and designed with the help of neural network. The main focus is on building autonomous robot and train it on a designed track with the help of neural network so that it can run autonomously without a controller or driver on that specific track. The robot will stream the video to Laptop which will then take decisions and send the data to raspberry pi which will then control the robot using motor driver. This motor driver will move the robot in required directions. Neural Network is used to train the model by first driving the robot on the specially designed track by labeling the images with the directions to be taken. After the model is trained it can make accurate predictions by processing the images on computer. This approach is better than conventional method which is done by extracting specific feature from images.

Links and sources

• Official / arXiv page

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