Mobile robots have shown immense potential and are expected to be widely used in the service industry. The importance of automatic navigation and voice cloning cannot be overstated as they enable functional robots to provide high-quality services. The objective of this work is to develop a control algorithm for the automatic navigation of a humanoid mobile robot called Cruzr, which is a service robot manufactured by Ubtech. Initially, a virtual environment is constructed in the simulation software Gazebo using Simultaneous Localization And Mapping (SLAM), and global path planning is carried out by means of local path tracking. The two-wheel differential chassis kinematics model is employed to ensure autonomous dynamic obstacle avoidance for the robot chassis. Furthermore, the mapping and trajectory generation algorithms developed in the simulation environment are successfully implemented on the real robot Cruzr. The performance of automatic navigation is compared between the Dynamic Window Approach (DWA) and Model Predictive Control (MPC) algorithms. Additionally, a mobile application for voice cloning is created based on a Hidden Markov Model, and the proposed Chatbot is also tested and deployed on Cruzr.

翻译：移动机器人展现出巨大潜力，有望在服务业得到广泛应用。自动导航与语音克隆技术的重要性不言而喻，它们使功能型机器人能够提供高质量服务。本工作的目标是为名为Cruzr的人形移动机器人开发自动导航控制算法，该机器人是优必选公司生产的服务机器人。首先，在仿真软件Gazebo中使用同步定位与建图技术构建虚拟环境，并通过局部路径跟踪实现全局路径规划。采用两轮差速底盘运动学模型，以确保机器人底盘实现自主动态避障。此外，在仿真环境中开发的建图与轨迹生成算法已成功在真实机器人Cruzr上实现。本文对比了动态窗口法与模型预测控制算法在自动导航方面的性能。同时，基于隐马尔可夫模型开发了语音克隆移动应用程序，所提出的聊天机器人也在Cruzr上进行了测试与部署。