  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.
