浙大机器人团队一年成果：硬件加惯性传感器，软件优化决策与预测。
ZJUNlict Extended Team Description Paper 2025
- 在机器人中集成IMU提升姿态精度和角速度规划
- 策略与CUDA模块优化，决策效率与球权预测能力显著提升
- 适合关注机器人运动控制与实时决策的科研人员
本文总结了浙江大学ZJUNlict团队过去一年在软硬件方面的进展。硬件方面，已完成在v2023机器人中集成惯性测量单元（IMU），以增强姿态精度与角速度规划能力。软件方面，对策略模块和CUDA加速模块进行了优化，显著提升了决策效率、球追逐预测及球权预测性能，使其更适应高速比赛节奏下的动态需求。
原文摘要 · Abstract (English)
This paper presents the ZJUNlict team's work over the past year, covering both hardware and software advancements. In the hardware domain, the integration of an IMU into the v2023 robot was completed to enhance posture accuracy and angular velocity planning. On the software side, key modules were optimized, including the strategy and CUDA modules, with significant improvements in decision making efficiency, ball pursuit prediction, and ball possession prediction to adapt to high-tempo game dynamics.
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