Electronics 2022, 11, 2982. https://doi.org/10.3390/electronics11192982 www.mdpi.com/journal/electronics Article A Novel, Energy‐Efficient Smart Speed Adaptation Based on the Gini Coefficient in Autonomous Mobile Robots Gürkan Gürgöze 1, * and İbrahim Türkoğlu 2 1 Department of Software Engineering, Institute of Science, Firat University, Elazig 23119, Turkey 2 Department of Software Engineering, Faculty of Technology, Firat University, Elazig 23119, Turkey * Correspondence: gurkangurgoze@gmail.com; Tel.: +90‐5053956815 Abstract: Using energy efficiently is an important parameter in mobile robots. The majority of the energy consumption takes place in the motors. As such, past studies have investigated how to re‐ duce the usage time of motors. Although the relationship between task energy and speed energy is considered in these studies, the qualification of the task, the amount of energy used, and the speed relation have not been taken into account as a whole. Parameters that affect each other in determin‐ ing the speed profile, such as the criteria by which energy saving is determined, the maximum speed limit, acceleration, the load, and the ground relation, have not been taken into account holistically. Another research focus concerns the need to distribute energy in a balanced manner, in accordance with the qualification of the task, and to ensure the movement occurs at the optimum speed. In this study, a new dynamic (online) intelligent speed and acceleration adaptation method, based on the task structure and energy balance, was developed for a specific path that overcomes the shortcom‐ ings of existing models. The Gini coefficient was used for the balanced distribution of energy. Sharp speed changes were prevented with the remaining path and the balanced distribution of the remain‐ ing energy. The current model is compared with the trapezoidal speed profile structure. Keywords: speed profile; energy balance; task speed relationship; acceleration profile 1. Introduction Mobile robots have limited energy resources. The efficient use of energy has emerged as an effective solution to this problem. At this point, many energy‐efficient task and mo‐ tion planning (short path planning, path smoothing, speed profiles, etc.) strategies have been developed [1‐3]. In both types of studies, the focus is on reducing the motor’s run‐ ning time and the power it consumes during travel in the mobile robot system. This is because, in these systems, the most consumption takes place in the motors. In terms of energy efficiency, task and short‐path studies are not sufficient solutions on their own. It is also necessary to consider the power consumption during travel [4,5]. The power con‐ sumption of the motors during travel relies heavily on a correct steering angle, speed and acceleration. In mission and motion planning studies, energy‐efficient speed optimiza‐ tions are neglected in terms of task durability and stability, or they are not considered as an effective parameter [6‐8]. Current energy‐efficient speed profile studies generally take into account the struc‐ ture of the road, but not the structure, durability, and stability of the task. Energy‐efficient speed profiles are based on distance and time. Straight and curved segments of the road play an important role in determining speed. Initially, a trapezoidal speed profile was used in applications [5,9]. However, Wang et al. revealed that this method is not optimal in terms of total energy [10]. Kim and Kim have separately presented energy‐efficient speed profiles based on a constant travel time for straight paths and a rotational trajectory. However, a speed profile combining both road sections has not been established [9,11]. Citation: Gürgöze, G.; Türkoğlu, İ.A Novel, Energy‐Efficient Smart Speed Adaptation Based on the Gini Coefficient in Autonomous Mobile Robots. Electronics 2022, 11, 2982. https://doi.org/10.3390/electronics 11192982 Academic Editor: Raed A. Abd‐Alhameed Received: 13 August 2022 Accepted: 18 September 2022 Published: 20 September 2022 Publisher’s Note: MDPI stays neu‐ tral with regard to jurisdictional claims in published maps and institu‐ tional affiliations. Copyright: © 2022 by the authors. Li‐ censee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and con‐ ditions of the Creative Commons At‐ tribution (CC BY) license (https://cre‐ ativecommons.org/licenses/by/4.0/).