Search Results for author:
Found 7 papers, 1 papers with code
Motion planning for off-road autonomous driving based on human-like cognition and weight adaptation
Then, based on human-like generated trajectories in different environments, we design a primitive-based trajectory planner that aims to mimic human trajectories and cost weight selection, generating trajectories that are consistent with the dynamics of off-road vehicles.
Leveraging Multi-stream Information Fusion for Trajectory Prediction in Low-illumination Scenarios: A Multi-channel Graph Convolutional Approach
The optical flow channel is applied to capture the pattern of relative motion between adjacent camera frames and modelled by Spatial-Temporal Graph Convolutional Network (ST-GCN).
Adaptive Decision Making at the Intersection for Autonomous Vehicles Based on Skill Discovery
But in uncertain environments, they are not reliable, so learning-based methods are proposed, especially reinforcement learning (RL) methods.
Orientation-Aware Planning for Parallel Task Execution of Omni-Directional Mobile Robot
Omni-directional mobile robot (OMR) systems have been very popular in academia and industry for their superb maneuverability and flexibility.
Autonomous Driving Strategies at Intersections: Scenarios, State-of-the-Art, and Future Outlooks
Due to the complex and dynamic character of intersection scenarios, the autonomous driving strategy at intersections has been a difficult problem and a hot point in the research of intelligent transportation systems in recent years.
High-precision target positioning system for unmanned vehicles based on binocular vision
In order to verify the effect of the system, this paper collects the accuracy and calculation time of the output results of the cylinder in different poses.
Learning and Generalizing Motion Primitives from Driving Data for Path-Tracking Applications
Therefore, the goal of this paper is to generate the prediction results of lateral commands with confidence regions according to the reference based on the learned motion primitives.
