Citation: Poonja, H.A.; Shah, M.S.A.; Uddin, R.; Kazmi, S.M.H.; Khan, H.; Ali, A.H.; Shirazi, M.A. Walking Algorithm Using Gait Analysis for Humanoid Robot. Eng. Proc. 2022, 20, 35. https://doi.org/10.3390/ engproc2022020035 Academic Editor: Saad Ahmed Qazi Published: 4 August 2022 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affil- iations. Copyright: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Proceeding Paper Walking Algorithm Using Gait Analysis for Humanoid Robot † Hasnain Ali Poonja, Muhammad Soleman Ali Shah, Riaz Uddin * , Syed Murtaza Hassan Kazmi, Humayun Khan, Abdullah Haider Ali and Muhammad Ayaz Shirazi Haptics, Human-Robotics and Condition Monitoring Lab (Affiliated with National Centre of Robotics and Automation), Department of Electrical Engineering, NED University of Engineering & Technology, Karachi 75270, Pakistan * Correspondence: riazuddin@neduet.edu.pk † Presented at the 7th International Electrical Engineering Conference, Karachi, Pakistan, 25–26 March 2022. Abstract: People have been fascinated with humanoid robots for over two decades. They are expected to assist and collaborate with humans in the future. However, due to the limitations and complications of bipedal humanoids’ walking mechanisms, this goal is still a long way off. In this paper, we have presented a walking mechanism algorithm using gait analysis to mimic the human walking pattern and applied that knowledge to enable the 17-DoF bipedal humanoid robot to walk in a constraint environment. The basic sequence of stance and swing phases of human locomotion is studied and used to control servo motors to perform the walking action of the robot. These robots can be useful for social interaction and collaborative tasks in the near future. Keywords: humanoid; bipedal robot; gait analysis; Arduino; social interaction 1. Introduction For decades, humanoid robots have been created and manufactured with inspiration from nature, particularly human anatomy and behavior [1]. However, due to the limits of bipedal robot control methods and modeling methodologies, the bipedal robot still needs some improvement as far as the walking algorithm is concerned. The movement of a robot along desired pathways that maintains stability and avoids collision with objects is one of the most critical aspects of bipedal locomotion [2]. The ability of a humanoid robot to move and execute tasks and activities in the same manner as humans is the most basic requirement for it to mimic human activity [3]. Walking is still one of the most difficult problems in bipedal humanoid robotics. Several studies have been published in this area in recent years. Using a detailed whole- body dynamic model of the robot, Hu et al. [2] provided an optimal control strategy that allows generating efficient walking movements. Piperakis et al. [4] introduced a novel cascade state estimation approach for estimating the three-dimensional (3-D) center of mass (CoM) of a humanoid robot in motion. Huan et al. [5] proposed a novel technique for bipedal robot gait creation called modified differential evolution (MDE) optimization, with the goal of allowing humanoid robots to walk more smoothly and steadily on flat platforms. Zhang et al. [6] used the Lagrange method to simulate the humanoid robot walking system in their research on dynamics for humanoid robots. Kim et al. [7] addressed the instability of walking humanoid robot with compliant motion control and proposed a model to generate real-time walk patterns that takes into account the robot’s motion control performance. Piperakis et al. [8] introduced an innovative unsupervised learning framework for gait phase estimation and then demonstrated its accuracy and usefulness in leg odometry using ground-truth data. Dong et al. [9] used a method based on a linear inverted pendulum model to investigate the walking problem of humanoid robots in their work. Chen et al. [10] used an adaptive fuzzy controller in their study to maintain the robot’s stability by adjusting the foot motion parameters under the minor torso’s motion Eng. Proc. 2022, 20, 35. https://doi.org/10.3390/engproc2022020035 https://www.mdpi.com/journal/engproc