让机器人自主导航并模仿人声，提升服务体验。
Automatic Navigation and Voice Cloning Technology Deployment on a Humanoid Robot
- 用SLAM建图+路径规划实现自主导航，支持动态避障。
- 实测对比DWA与MPC算法，验证导航性能差异。
- 基于隐马尔可夫模型开发语音克隆，已部署于真实机器人。
移动机器人在服务业具有巨大潜力，自动导航与语音克隆技术至关重要。本文针对优必选科技生产的仿人服务机器人Cruzr，开发其自主导航控制算法。首先在仿真软件Gazebo中利用同步定位与地图构建（SLAM）构建虚拟环境，并通过局部路径跟踪实现全局路径规划。采用双轮差速底盘运动学模型，确保机器人具备自主动态避障能力。同时，将仿真中的映射与轨迹生成算法成功部署至真实机器人Cruzr上。对比测试了动态窗口法（DWA）与模型预测控制（MPC）算法的导航表现。此外，基于隐马尔可夫模型（HMM）开发了一款语音克隆移动端应用，并将所设计的聊天机器人在Cruzr上完成测试与部署。
原文摘要 · Abstract (English)
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.
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