This report introduces our UniTeam agent - an improved baseline for the "HomeRobot: Open Vocabulary Mobile Manipulation" challenge. The challenge poses problems of navigation in unfamiliar environments, manipulation of novel objects, and recognition of open-vocabulary object classes. This challenge aims to facilitate cross-cutting research in embodied AI using recent advances in machine learning, computer vision, natural language, and robotics. In this work, we conducted an exhaustive evaluation of the provided baseline agent; identified deficiencies in perception, navigation, and manipulation skills; and improved the baseline agent's performance. Notably, enhancements were made in perception - minimizing misclassifications; navigation - preventing infinite loop commitments; picking - addressing failures due to changing object visibility; and placing - ensuring accurate positioning for successful object placement.

该研究介绍了我们的UniTeam代理——一个改进的基线模型，用于处理在陌生环境中的导航问题、新物体的操作问题以及开放词汇的物体识别问题。通过评估基线代理的性能，并改善感知、导航和操作技能，实现了在感知方面的缺陷最小化、导航方面的无限循环问题解决、取物方面的因物体能见度变化导致的失败问题解决以及放置方面的准确定位以成功放置物体。

UniTeam：开放词汇移动操控挑战赛