scholarly journals Parking Space Detection and Path Planning Based on VIDAR

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Yi Xu ◽  
Shanshang Gao ◽  
Guoxin Jiang ◽  
Xiaotong Gong ◽  
Hongxue Li ◽  
...  
Keyword(s):  
Path Planning ◽  
Detection Method ◽  
Parking Space ◽  
Planning Stage ◽  
Smooth Curves ◽  
Smooth Path ◽  
Detection Stage ◽  
Parking Space Detection ◽  
Automatic Parking ◽  
Simulation Results

The existing automatic parking algorithms often neglect the unknown obstacles in the parking environment, which causes a hidden danger to the safety of the automatic parking system. Therefore, this paper proposes parking space detection and path planning based on the VIDAR method (vision-IMU-based detection and range method) to solve the problem. In the parking space detection stage, the generalized obstacles are detected based on VIDAR to determine the obstacle areas, and then parking lines are detected by the Hough transform to determine the empty parking space. Compared with the parking detection method based on YOLO v5, the experimental results demonstrate that the proposed method has higher accuracy in complex parking environments with unknown obstacles. In the path planning stage, the path optimization algorithm of the A ∗ algorithm combined with the Bezier curve is used to generate smooth curves, and the environmental information is updated in real time based on VIDAR. The simulation results show that the method can make the vehicle efficiently avoid the obstacles and generate a smooth path in a dynamic parking environment, which can well meet the safety and stationarity of the parking requirements.

Local Path Planning for Dual-Arm Mobile Robot Shuttling within Truss

2012 ◽  
Vol 452-453 ◽  
pp. 1220-1224
Author(s):  
Wei Guo Wu ◽  
Peng Wu
Keyword(s):  
Path Planning ◽  
Mobile Robot ◽  
Planning Method ◽  
Planning Stage ◽  
Probabilistic Roadmaps ◽  
Local Path Planning ◽  
Smooth Path ◽  
Local Path ◽  
Two Stages ◽  
Dual Arm

A new local path planning method for dual-arm mobile robot shuttling within the truss is presented. Like the probabilistic roadmaps method, this method proceeds in two stages: preprocessing stage and path planning stage. In preprocessing stage, the workspace is divided into a set of non-overlapping cubical cells. The nodes in the free workspace are stored in a matrix. In path planning stage, three query strategies are adopted to search the path from start point to goal point. Take use of vertex query strategy, the smooth path can be acquired in a fraction of a second. The algorithm is simple, and is applicable to any static environment with convex obstacles.

scholarly journals Early Detection of Vacant Parking Spaces Using Dashcam Videos

2019 ◽  
Vol 33 ◽  
pp. 9613-9618 ◽  
Author(s):  
Ming-Che Wu ◽  
Mei-Chen Yeh
Keyword(s):  
Neural Network ◽  
Early Detection ◽  
Detection Method ◽  
Metropolitan Areas ◽  
Point Of View ◽  
Detection Methods ◽  
Parking Space ◽  
Large Dataset ◽  
Parking Space Detection ◽  
Indoor And Outdoor

A major problem in metropolitan areas is finding parking spaces. Existing parking guidance systems often adopt fixed sensors or cameras that cannot provide information from the driver’s point of view. Motivated by the advent of dashboard cameras (dashcams), we develop neural-network-based methods for detecting vacant parking spaces in videos recorded by a dashcam. Detecting vacant parking spaces in dashcam videos enables early detection of spaces. Different from conventional object detection methods, we leverage the monotonicity of the detection confidence with respect to the distance away of the approaching target parking space and propose a new loss function, which can not only yield improved detection results but also enable early detection. To evaluate our detection method, we create a new large dataset containing 5,800 dashcam videos captured from 22 indoor and outdoor parking lots. To the best of our knowledge, this is the first and largest driver’s view video dataset that supports parking space detection and provides parking space occupancy annotations.

scholarly journals Research Review on Parking Space Detection Method

Symmetry ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 128
Author(s):  
Yong Ma ◽  
Yangguo Liu ◽  
Lin Zhang ◽  
Yuanlong Cao ◽  
Shihui Guo ◽  
...  
Keyword(s):  
Detection Method ◽  
Urban Environments ◽  
Research Topic ◽  
Detection Methods ◽  
Research Review ◽  
Future Research ◽  
Parking Space ◽  
Reliable Detection ◽  
Parking Space Detection ◽  
Collision Avoidance System

The parking assist system is an essential application of the car’s active collision avoidance system in low-speed and complex urban environments, which has been a hot research topic in recent years. Parking space detection is an important step of the parking assistance system, and its research object is parking spaces with symmetrical structures in parking lots. By analyzing and investigating parking space information measured by the sensors, reliable detection of sufficient parking spaces can be realized. First, this article discusses the main problems in the process of detecting parking spaces, illustrating the research significance and current research status of parking space detection methods. In addition, it further introduces some parking space detection methods, including free-space-based methods, parking-space-marking-based methods, user-interface-based methods, and infrastructure-based methods, which are all under methods of parking space selection. Lastly, this article summarizes the parking space detection methods, which gives a clear direction for future research.

scholarly journals Smooth Path Planning for Robot Docking in Unknown Environment with Obstacles

Complexity ◽  
2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Peng Cui ◽  
Weisheng Yan ◽  
Rongxin Cui ◽  
Jiahui Yu
Keyword(s):  
Path Planning ◽  
Free Path ◽  
Integrated Approach ◽  
Tree Structure ◽  
Elastic Band ◽  
Band Theory ◽  
Smooth Path ◽  
Feasibility Evaluation ◽  
Simulation Results ◽  
Feasible Path

This paper presents an integrated approach to plan smooth path for robots docking in unknown environments with obstacles. To determine the smooth collision-free path in obstacle environment, a tree structure with heuristic expanding strategy is designed as the foundation of path planning in this approach. The tree employs 3D Dubins curves as its branches and foundation for path feasibility evaluation. For the efficiency of the tree expanding in obstacle environment, intermediate nodes and collision-free branches are determined inspired by the elastic band theory. A feasible path is chosen as the shortest series of branches that connects to the docking station after the sufficient expansion of the tree. Simulation results are presented to show the validity and feasibility of the proposed approach.

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