12. Development of Autonomous Navigation and Strategic Decision-Making in Robotic Soccer

Robotic soccer is an ideal testbed for integrating autonomous navigation, deep learning, and adaptive motion control in dynamic environments. This research aims to develop an advanced robotic soccer system based on the JetHexa hexapod robot, powered by the NVIDIA Jetson Nano B01 and operating on ROS. JetHexa leverages a suite of cutting-edge technologies-including mainstream deep learning frameworks (You Only Look Once (YOLO) model training, MediaPipe development, and TensorRT acceleration) alongside a 3D depth camera and Lidar sensor-to deliver high-precision 2D mapping, Real-Time Appearance-Based Mapping (RTAB)-3D mapping navigation, multi-point navigation, TEB path planning, and dynamic obstacle avoidance. The research is structured around three specific aims: 1) Autonomous Navigation Enhancement: to develop robust SLAM algorithms that exploit the combined data from the 3D depth camera and Lidar sensor to produce high-resolution field maps, thereby ensuring precise localization, reliable multi-point navigation, and effective dynamic obstacle avoidance in a rapidly changing soccer environment; 2) Deep Learning-Based Strategic Decision-Making: to integrate and optimize deep learning models that enable real-time detection and classification of critical game elements-such as the soccer ball, goals, and opposing players-using frameworks like YOLO and MediaPipe accelerated by TensorRT, thus facilitating intelligent and context-aware decision-making during gameplay;
and 3) Adaptive Motion Control and Kinematics: to implement advanced inverse kinematics algorithms that support dynamic gait switching between tripod and ripple patterns and enable adaptive motion control, including specialized maneuvers like moonwalking, through the fine-tuning of parameters such as pitch, roll, direction, speed, height, and stride to maintain optimal stability and maneuverability across variable soccer field terrains.

Autonomous Navigation and Strategic Decision-Making

Deep Learning 

Mid-Level

Knowledge

Women in Statistics and Data Science 2025