We report an improvements to NeurIPS 2023 HomeRobot: Open Vocabulary Mobile Manipulation (OVMM) Challenge reinforcement learning baseline. More specifically, we propose more accurate semantic segmentation module, along with better place skill policy, and high-level heuristic that outperforms the baseline by 2.4% of overall success rate (sevenfold improvement) and 8.2% of partial success rate (1.75 times improvement) on Test Standard split of the challenge dataset. With aforementioned enhancements incorporated our agent scored 3rd place in the challenge on both simulation and real-world stages.

翻译：我们报告了针对NeurIPS 2023 HomeRobot：开放词汇移动操控（OVMM）挑战赛的强化学习基准模型改进方案。具体而言，我们提出了更精确的语义分割模块，结合更优的放置技能策略及高层级启发式方法，在挑战赛数据集的测试标准集上实现了总体成功率2.4%的提升（提升七倍）和部分成功率8.2%的提升（提升1.75倍），相较于基准模型取得显著优势。采用上述增强方案后，我们的智能体在模拟和真实场景两个阶段均获得了该挑战赛第三名的成绩。