Gait planning for the humanoid robot is a very essential and basic requirement. The humanoid robot is balanced at two feet; therefore, special attention is required for gait analysis for the execution of assigned tasks. In this paper, the linear inverted pendulum (LIPM) model is considered to simplify the study and to obtain better gait planning of humanoid robot NAO. Center of mass (COM) and zero moment point (ZMP) criterion are applied with the LIPM model for a better understanding of selecting the step length and period. In addition, a PSO (particle swarm optimization) tuned PID (proportional–integral–derivative) controller has been implemented. Sensory data such as the location of obstacles and the target along with the desired trajectory aided inverse kinematics have been embedded to the conventional PID controller, which provides an interim angle to start the navigation. This interim angle has been carried forward to the PSO technique accompanied by the desired trajectory. It tunes the parameters of the conventional PID controller and provides an optimum turning angle, which avoids obstacles and increases the stabilization of the robot while crossing it. It reduces travel time and shortens travel length. PSO technique minimizes the computational complexity and number of iteration because it requires fewer tuning parameters. Simulations are executed on the simulated NAO robot for the conventional PID controller and the proposed controller. To ratify its findings, experiments are carried out on a real NAO robot in laboratory conditions for both the conventional PID controller and the proposed controller. Simulation and experimental results are presenting a good agreement among each other with deviation under 6%. Applying the PSO tuned PID controller provides a predictable gait and reduces the stabilization time and essentially eliminating the overshoot by 25%. A comparative study with various controllers is performed, and the credibility of the evaluated result has been examined using statistical analysis. The proposed controller has been compared with a previously developed technique to ensure its robustness.

人形机器人的步态规划是一个非常必要和基本的要求。人形机器人两脚平衡；因此，在执行指定任务时需要特别注意步态分析。在本文中，线性倒立摆（LIPM）模型被认为是为了简化研究并获得仿人机器人NAO更好的步态规划。质心 (COM) 和零力矩点 (ZMP) 准则与 LIPM 模型一起应用，以便更好地理解选择步长和周期。此外，还实施了 PSO（粒子群优化）调谐 PID（比例-积分-微分）控制器。诸如障碍物位置和目标以及所需轨迹辅助逆运动学等感官数据已嵌入到传统的 PID 控制器中，它提供了一个过渡角度来开始导航。这个中间角度已经被推进到 PSO 技术，伴随着所需的轨迹。它可以调整传统 PID 控制器的参数并提供最佳转弯角度，从而避免障碍物并增加机器人在穿越时的稳定性。它减少了旅行时间并缩短了旅行长度。PSO 技术最大限度地减少了计算复杂性和迭代次数，因为它需要更少的调整参数。对传统 PID 控制器和建议控制器的模拟 NAO 机器人进行仿真。为了验证其发现，在实验室条件下对真实的 NAO 机器人对传统 PID 控制器和建议的控制器进行了实验。仿真和实验结果显示出良好的一致性，偏差在 6% 以下。应用 PSO 调谐 PID 控制器可提供可预测的步态并减少稳定时间并基本上消除 25% 的过冲。与各种控制器进行了比较研究，并使用统计分析检查了评估结果的可信度。所提出的控制器已与先前开发的技术进行了比较，以确保其鲁棒性。并对评价结果的可信度进行了统计分析。所提出的控制器已与先前开发的技术进行了比较，以确保其鲁棒性。并对评价结果的可信度进行了统计分析。所提出的控制器已与先前开发的技术进行了比较，以确保其鲁棒性。