Real-Time Optimal Path Generation Avoiding Turbulent Areas Using LIDAR Information

2017 ◽  
Vol 65 (6) ◽  
pp. 227-234
Author(s):  
Kotaro SHOMURA ◽  
Takeshi TSUCHIYA
Keyword(s):  
Real Time ◽  
Optimal Path ◽  
Path Generation ◽  
Time Optimal

Research on Real-Time Optimal Path Algorithm of Urban Transport

2014 ◽  
Vol 12 (5) ◽  
Author(s):  
Jie Zhang ◽  
Jianchun Li ◽  
Xiaoyan Fan ◽  
Zhuo Deng
Keyword(s):  
Real Time ◽  
Optimal Path ◽  
Urban Transport ◽  
Time Optimal

Non-Collision Path Planning of a Payload in Crane Operating Space

2013 ◽  
Vol 198 ◽  
pp. 559-564 ◽  
Author(s):  
Jaroslaw Smoczek ◽  
Janusz Szpytko ◽  
Pawel Hyla
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Optimal Path ◽  
Manufacturing Processes ◽  
Automated Manufacturing ◽  
Star Graph ◽  
Graph Searching ◽  
Optimal Path Planning ◽  
Time Optimal ◽  
Operating Space

The problem of ensuring the safe and efficient cranes operations in automated manufacturing processes involves the automation of the operating workspace identification, non-collision and time-optimal path planning, and real-time following a payload along the determined path by crane motion mechanisms with expected precision. The paper describes the stereo vision based system used for identification of workspace of the laboratory scaled overhead travelling crane. The time-optimal trajectory of a payload is determined by using the A-star graph searching algorithm, and next real-time trucking by PLC-based crane control system.

scholarly journals AlphaPilot: autonomous drone racing

2021 ◽  
Author(s):  
Philipp Foehn ◽  
Dario Brescianini ◽  
Elia Kaufmann ◽  
Titus Cieslewski ◽  
Mathias Gehrig ◽  
...  
Keyword(s):  
Real Time ◽  
Trajectory Planning ◽  
Nonlinear Filtering ◽  
Optimal Trajectory ◽  
Optimal Path ◽  
Data Abstraction ◽  
State Estimate ◽  
World Championship ◽  
Time Optimal ◽  
Optimal Trajectory Planning

AbstractThis paper presents a novel system for autonomous, vision-based drone racing combining learned data abstraction, nonlinear filtering, and time-optimal trajectory planning. The system has successfully been deployed at the first autonomous drone racing world championship: the 2019 AlphaPilot Challenge. Contrary to traditional drone racing systems, which only detect the next gate, our approach makes use of any visible gate and takes advantage of multiple, simultaneous gate detections to compensate for drift in the state estimate and build a global map of the gates. The global map and drift-compensated state estimate allow the drone to navigate through the race course even when the gates are not immediately visible and further enable to plan a near time-optimal path through the race course in real time based on approximate drone dynamics. The proposed system has been demonstrated to successfully guide the drone through tight race courses reaching speeds up to $${8}\,{\hbox {m}/\hbox {s}}$$ 8 m / s and ranked second at the 2019 AlphaPilot Challenge.

scholarly journals Research on Real-Time Optimal Path Planning Model and Algorithm for Ship Block Transportation in Shipyard

2020 ◽  
Vol 8 (12) ◽  
pp. 991
Author(s):  
Chong Wang ◽  
Kang Wang ◽  
Jiabin Tao ◽  
Yongqing Zhou
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Optimal Path ◽  
High Energy ◽  
Dijkstra Algorithm ◽  
The Real ◽  
Security Issues ◽  
Time Path ◽  
Time Optimal ◽  
Shortest Path Algorithms

Special vehicles called transporters are used to deliver heavy blocks in the shipyard. With the development and application of information and communication technology in shipyards, the real-time positioning and ship blocks online scheduling system for transporters are being developed. The real-time path planning of transporters is important for maintaining the overall production schedule of ship blocks. Because of the large volume and heavy weight of ship blocks, there may be some problems, such as high energy consumption, block deformation and other security issues, when transporters loading a block make a turn. So, fewer turns of the transporters are also important to make a block transportation schedule. The minimum driving distance and fewer turns are considered simultaneously for transporter real-time path planning in this paper. A hybrid model considering the number of turns and the optimal path of the transporter is constructed. Moreover, the optimal scheduling model, considering path missing, is also discussed. Several shortest path algorithms are analyzed, which show that the Dijkstra algorithm is the best way to solve this model. From the attained simulation results, we demonstrate that the proposed model and algorithm have the ability to effectively solve real-time path planning for the ship block transportation in shipyards.

Time-optimal path planning: Real-time sea exercises

2017 ◽  
Author(s):  
Deepak N. Subramani ◽  
Pierre F. J. Lermusiaux ◽  
Patrick J. Haley ◽  
Chris Mirabito ◽  
Sudip Jana ◽  
...  
Keyword(s):  
Path Planning ◽  
Real Time ◽  
Optimal Path ◽  
Optimal Path Planning ◽  
Time Optimal
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