Google Brax locomotion environments

该数据集使用了谷歌Brax物理引擎，包含了具有挑战性的运动任务，如Walker、Ant和Humanoid等环境。数据集评估了包括脚步接触、速度、跳跃和角度等多种特征函数。此外，该数据集还包含了有助于评估QDAC算法在不同运动场景中性能和适应性的特征。规模上，数据集涵盖了多个环境，并具有多种特征。其任务是对连续控制任务进行评估和适应。

This dataset utilizes the Google Brax physics engine and encompasses challenging locomotion tasks with environments such as Walker, Ant, and Humanoid. Multiple feature functions including foot contact, velocity, jump performance, and joint angles are evaluated in this dataset. Additionally, the dataset contains features that assist in assessing the performance and adaptability of the QDAC algorithm across various locomotion scenarios. In terms of scale, the dataset covers multiple environments and incorporates diverse features. Its core objective is to evaluate and adapt to continuous control tasks.