J Intell Robot Syst (2015) 79:237–257 DOI 10.1007/s10846-014-0124-8 Optimal Path Planning Generation for Mobile Robots using Parallel Evolutionary Artificial Potential Field Oscar Montiel · Roberto Sep ´ ulveda · Ulises Orozco-Rosas Received: 14 October 2013 / Accepted: 5 September 2014 / Published online: 20 September 2014 © Springer Science+Business Media Dordrecht 2014 Abstract In this paper, we introduce the concept of Parallel Evolutionary Artificial Potential Field (PEAPF) as a new method for path planning in mobile robot navigation. The main contribution of this pro- posal is that it makes possible controllability in com- plex real-world sceneries with dynamic obstacles if a reachable configuration set exists. The PEAPF out- performs the Evolutionary Artificial Potential Field (EAPF) proposal, which can also obtain optimal solu- tions but its processing times might be prohibitive in complex real-world situations. Contrary to the orig- inal Artificial Potential Field (APF) method, which cannot guarantee controllability in dynamic environ- ments, this innovative proposal integrates the original APF, evolutionary computation and parallel computa- tion for taking advantages of novel processors archi- tectures, to obtain a flexible path planning navigation method that takes all the advantages of using the APF and the EAPF, strongly reducing their disadvantages. We show comparative experiments of the PEAPF against the APF and the EAPF original methods. O. Montiel () · R. Sep´ ulveda · U. Orozco-Rosas Instituto Polit´ ecnico Nacional-CITEDI, Av. del Parque No. 1310, Mesa de Otay, C.P. 22510, Tijuana, Baja California, M´ exico e-mail: oross@ipn.mx R. Sep ´ ulveda e-mail: rsepulvedac@ipn.mx U. Orozco-Rosas e-mail: uorozco@citedi.mx The results demonstrate that this proposal overcomes both methods of implementation; making the PEAPF suitable to be used in real-time applications. Keywords Mobile robot navigation · Path planning · Artificial potential field · APF · PEAPF · Parallel evolutionary computation 1 Introduction At the present time, robotics is one of the most important technologies since it is a fundamental part in automation and manufacturing process. In partic- ular, there is an increasing demand of autonomous mobile robots (MRs) in various fields of applica- tion, such as material transport, cleaning, surveillance, monitoring of dangerous radioactive sites and mili- tary applications; but the potential of applications for MRs do not include only special missions, they are also being used as guides in hospitals, schools, muse- ums and many other home applications. These MRs must interact with their surroundings, to accomplish their missions; the environment may be subject to changes on it, and unforeseen. This work addresses the problem of autonomous navigation of an MR to take it from one position to another one without the assistance of a human operator, in particular, find- ing the best reachable set of MR configurations to accomplish its mission. To solve this problem, it is necessary to have a methodology that allows guiding