An optimization approach to trajectory generation for autonomous vehicle following

Author(s):  
Dennis Fassbender ◽  
Benjamin C. Heinrich ◽  
Thorsten Luettel ◽  
Hans-Joachim Wuensche
Author(s):  
José A. Fernández-León ◽  
Gerardo G. Acosta ◽  
Miguel A. Mayosky ◽  
Oscar C. Ibáñez

This work is intended to give an overview of technologies, developed from an artificial intelligence standpoint, devised to face the different planning and control problems involved in trajectory generation for mobile robots. The purpose of this analysis is to give a current context to present the Evolutionary Robotics approach to the problem, which is now being considered as a feasible methodology to develop mobile robots for solving real life problems. This chapter also show the authors’ experiences on related case studies, which are briefly described (a fuzzy logic based path planner for a terrestrial mobile robot, and a knowledge-based system for desired trajectory generation in the Geosub underwater autonomous vehicle). The development of different behaviours within a path generator, built with Evolutionary Robotics concepts, is tested in a Khepera© robot and analyzed in detail. Finally, behaviour coordination based on the artificial immune system metaphor is evaluated for the same application.


Author(s):  
Liwen Guan ◽  
Lu Chen

Purpose This paper aims to present a new trajectory optimization approach targeting spray painting applications that satisfies the paint thickness requirements of complex-free surfaces. Design/methodology/approach In this paper, a new trajectory generation approach is developed to optimize the transitional segments at the junction of adjacent patches for straight line, convex arc and concave arc combinations based on different angles between normal vectors of patches. In addition, the paint parameters including the paint gun velocity, spray height and the distance between adjacent trajectories have been determined in the generation approach. Then a thickness distribution model is established to simulate the effectiveness of trajectory planning. Findings The developed approach was applied to a complex-free surface of various curvatures, and the analysis results of the trajectory optimization show that adopting different transitional segment according to the angle between normal vectors can obtain the optimal trajectory. Based on the simulation and experimental validation results, the proposed approach is effective at improving paint thickness uniformity, and the obtained results are consistent with the simulation results, meaning that the simulation model can be used to predict the actual paint performance. Originality/value This paper discusses a new trajectory generation approach to decrease the thickness error values to satisfy spray paint requirements. According to the successfully performed simulation and experimental results, the approach is useful and practical in overcoming the challenge of improving the paint thickness quality on complex-free surface.


Author(s):  
Mohammad Goli ◽  
Azim Eskandarian

Problem of autonomous vehicle platooning in an automated highway setting has drawn many attentions, both in academia and industry, during last two decades. This paper studies the problem of vehicle platooning with a particular focus on merging control algorithm when one or several vehicle(s) merge(s) from the adjacent lane into the main vehicle platoon under longitudinal control. Different longitudinal controllers have been compared. A practical novel multi-vehicle merge-in strategy and an adaptive lateral trajectory generation method have been proposed. The proposed approach is then tested and verified in our newly developed simulation platform SimPlatoon.


2009 ◽  
Vol 15 ◽  
pp. 73-78 ◽  
Author(s):  
J. Ramírez-Gordillo ◽  
J.J. Muñoz-César ◽  
A. Gómez-Terán ◽  
A. Valencia-Lazcano ◽  
A.L. Soria-Moya

This work presents the problem of trajectory generation based on the use of artificial potential fields associated to articulated robotic manipulators, in order to find a trajectory so that a manipulator reaches a goal from an initial position without colliding with obstacles within its workspace. The search of a continuous sequence of collision-free configurations between an initial configuration and the final position implies the exploration of a non-linear solution space which can be described and solved with an optimization approach. It does not take into account the use of complex mathematics in an analytical or numerical solution of the inverse kinematics, where are shown manifolds solutions as a result of the angular displacements of each joint of the robot. The genetic algorithm used as strategy, reduces the complexity of the problem, because the geometric connection equations are obtained systematically. In addition, the artificial potential field simulates the attraction and repulsion forces between the goal and the obstacles, where the goal is identified as the global minimum and the obstacles as restricted points. Altogether the potential field and the genetic algorithm generate trajectories for the robot among the obstacles through the design of an appropriate fitness function that effectively drives the manipulator to the desired while avoiding collide with the obstacles.


Robotica ◽  
1993 ◽  
Vol 11 (4) ◽  
pp. 309-314 ◽  
Author(s):  
S.S. Lee ◽  
J.H. Williams ◽  
P.J. Rayment

SUMMARYThis paper presents a trajectory generation method using smooth functions for an automatic guidance system of an autonomous vehicle with two differentially driven wheels within structured environments. A control algorithm based on an incrementally generated smooth trajectory gives a good performance when implemented on an experimental vehicle.


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