2A1-Q01 Trajectory Planning of Automobiles for Collision Avoidance by Using the Hydrodynamic Potential(Car Robotics & ITS)

2013 ◽  
Vol 2013 (0) ◽  
pp. _2A1-Q01_1-_2A1-Q01_4
Author(s):  
Naoki SHIBATA ◽  
Seiji SUGIYAMA ◽  
Takahiro WADA
Author(s):  
Juan-Bautista Tomas-Gabarron ◽  
Felipe Garcia-Sanchez ◽  
Antonio-Javier Garcia-Sanchez ◽  
Joan Garcia-Haro

Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.


Robotica ◽  
2013 ◽  
Vol 31 (8) ◽  
pp. 1351-1359 ◽  
Author(s):  
Shuang Liu ◽  
Dong Sun

SUMMARYThe present paper presents a new approach to a leader–follower-based dynamic trajectory planning for multirobot formation. A near-optimal trajectory is generated for each robot in a decentralized manner. The main contributions of the current paper are the proposal of a new objective function that considers both collision avoidance and formation requirement for the trajectory generation, and an analytical solution of trajectory parameters in the trajectory optimization. Simulations and experiments on multirobots are performed to demonstrate the effectiveness of the proposed approach to the multirobot formation in a dynamic environment.


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