Title: Robustness towards application of multi-objective optimisation for autonomous off-road vehicle on rough terrain
Authors: Mahesh Kumar Isher; He Xu; He Long
Addresses: College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China. ' College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China. ' College of Mechanical and Electrical Engineering, Harbin Engineering University, Harbin 150001, China
Abstract: Force distribution emerged as a major concern in the case of autonomous vehicle because of its importance of control in unknown environment. Tipover and deadlocks are vital problems arising in remote operations of the vehicle. An evolutionary approach was used to attain multiple trade-off solutions, which minimised force variations along with the maximisation of draw bar pull and torque within optimisation of available power. Robustness towards Pareto optimal solutions was analysed as a major concern. Furthermore, different Pareto fronts was obtained with different noise induced into the terrain characteristics mainly soil cohesion (c), shear deformation modulus (k) and internal friction angle (phi). Result presented shows that the noise intensity > 2% impacts greater in the solution quality should be taken as less robust solution and can be implemented to the control algorithm.
Keywords: robustness; noise impact; Pareto optimal solutions; genetic algorithms; GAs; multi-objective optimisation; MOO; autonomous vehicles; rough terrain; off-road vehicles; soil cohesion; shear deformation; internal friction angle; vehicle tipover; deadlocks; remote operation; vehicle control.
International Journal of Mechatronics and Automation, 2012 Vol.2 No.2, pp.103 - 111
Available online: 25 Jul 2012 *Full-text access for editors Access for subscribers Purchase this article Comment on this article