Rulin Huang

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This paper describes a real-time motion planner based on the drivers' visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers' visual search behavior in the framework of RRT motion planner. RRT is an incremental(More)
As an effective environment representation method, the obstacle occupancy grid has been widely applied on the autonomous vehicle, providing evidence for the behavior decision and path planning of autonomous vehicle. In this paper, a new obstacle occupancy grid named space-time occupancy grid map is presented. This map pays more attention on the dynamic(More)
In this paper, a novel intent inference based dynamic obstacle avoidance method is described that is effective for both normal moving obstacles and maneuvering obstacles, therefore taking advantages of information from different sensors and electronic map. Unlike many of the methods discussed in literature our approach is based on inferring the intent of(More)
Driving through dynamically changing traffic scenarios is a highly challenging task for autonomous vehicles, especially on urban roadways. Prediction of surrounding vehicles’ driving behaviors plays a crucial role in autonomous vehicles. Most traditional driving behavior prediction models work only for a specific traffic scenario and cannot be adapted to(More)
This paper addresses the forward displacement of a special class of the 6/6-SPS Stewart manipulators in which the moving platform and the base one are two dissimilar semisymmetrical hexagons. After proposing a mathematical model of the forward displacement of this special class of the Stewart manipulators, a multivariate polynomial equations set in the(More)
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