Efficient trajectory of a car-like mobile robot. Issue 2 (18th March 2019)

• Record Type: Journal Article
• Authors: Valero, Francisco; Rubio, Francisco; Besa, Antonio José; Llopis-Albert, Carlos
• Is Part Of: Industrial robot. Volume 46:Issue 2(2019)
• Page Start: 211
• Page End: 222
• Publication Date: 2019-03-18
• Subjects: Optimization -- Obstacle avoidance -- Car-like robot navigation -- Robot dynamics; Robots, Industrial -- Periodicals; Machinery in the workplace -- Periodicals; 629.892
• DOI: 10.1108/IR-10-2018-0214
• Languages: English
• ISSNs: 0143-991X

Abstract

Abstract : Purpose: The purpose is to create an algorithm that optimizes the trajectories that an autonomous vehicle must follow to reduce its energy consumption and reduce the emission of greenhouse gases. Design/methodology/approach: An algorithm is presented that respects the dynamic constraints of the robot, including the characteristics of power delivery by the motor, the behaviour of the tires and the basic inertial parameters. Using quadratic sequential programming with distributed and non-monotonous search direction (Quadratic Programming Algorithm with Distributed and Non-Monotone Line Search), an optimization algorithm proposed and developed by Professor K. Schittkowski is implemented. Findings: Relations between important operating variables have been obtained, such as the evolution of the autonomous vehicle's velocity, the driving torque supplied by the engine and the forces acting on the tires. In a subsequent analysis, the aim is to analyse the relationship between trajectory made and energy consumed and calculate the reduction of greenhouse gas emissions. Also this method has been checked against another different methodology commented on in the references. Research limitations/implications: The main limitation comes from the modelling that has been done. As greater is the mechanical systems analysed, more simplifying hypotheses should be introduced to solve the corresponding equations with the current computers. However, the solutions are obtained and they can be used qualitatively to draw conclusions. Practical implications: One main objective is to obtain guidelines to reduce greenhouse gas emissions by reducing energy consumption in the realization of autonomous vehicles' trajectories. The first step to achieve that is to obtain a good model of the autonomous vehicle that takes into account not only its kinematics but also its dynamic properties, and to propose an optimization process that allows to minimize the energy consumed. In this paper, important relationships between work variables have been obtained. Social implications: The idea is to be friendly with nature and the environment. This algorithm can help by reducing an instance of greenhouse gases. Originality/value: Originality comes from the fact that we not only look for the autonomous vehicle's modelling, the simulation of its motion and the analysis of its working parameters, but also try to obtain from its working those guidelines that are useful to reduce the energy consumed and the contamination capability of these autonomous vehicles or car-like robots.