{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T18:39:57Z","timestamp":1772044797150,"version":"3.50.1"},"reference-count":28,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T00:00:00Z","timestamp":1691539200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Robot. AI"],"abstract":"<jats:p><jats:bold>Introduction:<\/jats:bold> The challenge of navigating a Mobile robot in dynamic environments has grasped significant attention in recent years. Despite the available techniques, there is still a need for efficient and reliable approaches that can address the challenges of real-time near optimal navigation and collision avoidance.<\/jats:p><jats:p><jats:bold>Methods:<\/jats:bold> This paper proposes a novel Log-concave Model Predictive Controller (MPC) algorithm that addresses these challenges by utilizing a unique formulation of cost functions and dynamic constraints, as well as a convergence criterion based on Lyapunov stability theory. The proposed approach is mapped onto a novel recurrent neural network (RNN) structure and compared with the CVXOPT optimization tool. The key contribution of this study is the combination of neural networks with model predictive controller to solve optimal control problems locally near the robot, which offers several advantages, including computational efficiency and the ability to handle nonlinear and complex systems.<\/jats:p><jats:p><jats:bold>Results:<\/jats:bold> The major findings of this study include the successful implementation and evaluation of the proposed algorithm, which outperforms other methods such as RRT, A-Star, and LQ-MPC in terms of reliability and speed. This approach has the potential to facilitate real-time navigation of mobile robots in dynamic environments and ensure a feasible solution for the proposed constrained-optimization problem.<\/jats:p>","DOI":"10.3389\/frobt.2023.1226028","type":"journal-article","created":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T09:04:05Z","timestamp":1691571845000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":9,"title":["Optimal predictive neuro-navigator design for mobile robot navigation with moving obstacles"],"prefix":"10.3389","volume":"10","author":[{"given":"Mahsa","family":"Mohaghegh","sequence":"first","affiliation":[]},{"given":"Samaneh-Alsadat","family":"Saeedinia","sequence":"additional","affiliation":[]},{"given":"Zahra","family":"Roozbehi","sequence":"additional","affiliation":[]}],"member":"1965","published-online":{"date-parts":[[2023,8,9]]},"reference":[{"key":"B1","doi-asserted-by":"publisher","first-page":"4992","DOI":"10.3390\/s23114992","article-title":"Model-predictive control for omnidirectional mobile robots in logistic environments based on object detection using CNNs","volume":"23","author":"Achirei","year":"2023","journal-title":"Sensors"},{"key":"B2","first-page":"2084","article-title":"Sampling-based nonlinear MPC of neural network dynamics with application to autonomous vehicle motion planning","author":"Askari","year":"2022"},{"key":"B3","first-page":"3965","article-title":"Neural path planning: Fixed time, near-optimal path generation via oracle imitation","author":"Bency","year":"2019"},{"key":"B4","article-title":"Parameter estimation method using an extended Kalman filter","author":"Blanchard","year":"2007"},{"key":"B5","doi-asserted-by":"publisher","first-page":"2376","DOI":"10.1109\/tits.2019.2918176","article-title":"Longitudinal collision avoidance and lateral stability adaptive control system based on MPC of autonomous vehicles","volume":"21","author":"Cheng","year":"2019","journal-title":"IEEE Trans. Intelligent Transp. Syst."},{"key":"B6","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1007\/s10107-021-01631-4","article-title":"A primal-dual interior-point algorithm for nonsymmetric exponential-cone optimization","volume":"194","author":"Dahl","year":"2022","journal-title":"Math. Program."},{"key":"B7","first-page":"279","article-title":"Footstep planning on uneven terrain with mixed-integer convex optimization","author":"Deits","year":"2014"},{"key":"B8","doi-asserted-by":"publisher","first-page":"e0275100","DOI":"10.1371\/journal.pone.0275100","article-title":"A path planning approach for mobile robots using short and safe Q-learning","volume":"17","author":"Du","year":"2022","journal-title":"Plos one"},{"key":"B9","doi-asserted-by":"publisher","first-page":"2279","DOI":"10.1016\/s0031-3203(01)00178-9","article-title":"Image processing with neural networks\u2014A review","volume":"35","author":"Egmont-Petersen","year":"2002","journal-title":"Pattern Recognit."},{"key":"B10","doi-asserted-by":"publisher","first-page":"9060","DOI":"10.1016\/j.jksuci.2022.08.031","article-title":"Robust mobile robot navigation in cluttered environments based on hybrid adaptive neuro-fuzzy inference and sensor fusion","volume":"34","author":"Haider","year":"2022","journal-title":"J. King Saud University-Computer Inf. Sci."},{"key":"B11","doi-asserted-by":"publisher","first-page":"448","DOI":"10.3390\/vehicles3030027","article-title":"A survey of path planning algorithms for mobile robots","volume":"3","author":"Karur","year":"2021","journal-title":"Vehicles"},{"key":"B12","first-page":"1","article-title":"End-to-end deep learning for autonomous navigation of mobile robot","author":"Kim","year":"2018"},{"key":"B13","doi-asserted-by":"publisher","first-page":"2748","DOI":"10.3390\/pr10122748","article-title":"Mobile robot navigation using deep reinforcement learning","volume":"10","author":"Lee","year":"2022","journal-title":"Processes"},{"key":"B14","doi-asserted-by":"publisher","first-page":"7769","DOI":"10.1016\/j.ifacol.2017.08.1050","article-title":"Learning-based Nonlinear Model Predictive Control * *The authors would like to ackowledge to the Spanish MINECO Grant PRX15-00300 and projects DPI2013-48243-C2-2-R and DPI2016-76493-C3-1-R as well as to the Engineering and Physical Research Council, grant no. EP\/J012300\/1 for funding this work","volume":"50","author":"Limon","year":"2017","journal-title":"IFAC-PapersOnLine"},{"key":"B15","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1155\/2015\/608015","article-title":"Motion control design for an omnidirectional mobile robot subject to velocity constraints","volume":"2015","author":"Pe\u00f1aloza-Mej\u00eda","year":"2015","journal-title":"Math. Problems Eng."},{"key":"B16","doi-asserted-by":"publisher","first-page":"172988142092167","DOI":"10.1177\/1729881420921672","article-title":"A novel mobile robot navigation method based on deep reinforcement learning","volume":"17","author":"Quan","year":"2020","journal-title":"Int. J. Adv. Robotic Syst."},{"key":"B17","first-page":"507","article-title":"UAV path planning employing MPC-reinforcement learning method considering collision avoidance","author":"Ramezani","year":"2023"},{"key":"B18","doi-asserted-by":"publisher","first-page":"9716","DOI":"10.1177\/09544062221095414","article-title":"The synergy of the multi-modal MPC and Q-learning approach for the navigation of a three-wheeled omnidirectional robot based on the dynamic model with obstacle collision avoidance purposes","volume":"236","author":"Saeedinia","year":"2022","journal-title":"Proc. Institution Mech. Eng. Part C J. Mech. Eng. Sci."},{"key":"B19","doi-asserted-by":"publisher","first-page":"2397","DOI":"10.1109\/lra.2023.3246839","article-title":"Real-time neural MPC: Deep learning model predictive control for quadrotors and agile robotic platforms","volume":"8","author":"Salzmann","year":"2023","journal-title":"IEEE Robotics Automation Lett."},{"key":"B20","first-page":"7629","article-title":"Learning high-level policies for model predictive control","author":"Song","year":"2020"},{"key":"B21","article-title":"Model predictive path tracking control for automated road vehicles: A review","author":"Stano","year":"2022","journal-title":"Annu. Rev. Control"},{"key":"B22","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.neucom.2017.04.075","article-title":"Artificial neural networks used in optimization problems","volume":"272","author":"Villarrubia","year":"2018","journal-title":"Neurocomputing"},{"key":"B23","first-page":"614","article-title":"A LiDAR based end to end controller for robot navigation using deep neural network","author":"Wang","year":"2017"},{"key":"B24","first-page":"987","article-title":"Optimal trajectory generation for dynamic street scenarios in a frenet frame","author":"Werling","year":"2010"},{"key":"B25","doi-asserted-by":"publisher","first-page":"24884","DOI":"10.1109\/access.2021.3057485","article-title":"Unmanned aerial vehicle path planning algorithm based on deep reinforcement learning in large-scale and dynamic environments","volume":"9","author":"Xie","year":"2021","journal-title":"IEEE Access"},{"key":"B26","unstructured":"Learning model predictive controllers with real-time attention for real-world navigation\n            XiaoX.\n          2022"},{"key":"B27","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1007\/s10846-009-9359-1","article-title":"An efficient path planning and control algorithm for RUAV\u2019s in unknown and cluttered environments","volume":"57","author":"Yang","year":"2010","journal-title":"J. Intelligent Robotic Syst."},{"key":"B28","doi-asserted-by":"publisher","first-page":"269","DOI":"10.1016\/j.ast.2015.09.037","article-title":"Real-time path planning of unmanned aerial vehicle for target tracking and obstacle avoidance in complex dynamic environment","volume":"47","author":"Yao","year":"2015","journal-title":"Aerosp. Sci. Technol."}],"container-title":["Frontiers in Robotics and AI"],"original-title":[],"link":[{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frobt.2023.1226028\/full","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,9]],"date-time":"2023-08-09T09:04:09Z","timestamp":1691571849000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.frontiersin.org\/articles\/10.3389\/frobt.2023.1226028\/full"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,9]]},"references-count":28,"alternative-id":["10.3389\/frobt.2023.1226028"],"URL":"https:\/\/doi.org\/10.3389\/frobt.2023.1226028","relation":{},"ISSN":["2296-9144"],"issn-type":[{"value":"2296-9144","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,9]]},"article-number":"1226028"}}