# HomeRobot Open Vocabulary Mobile Manipulation Challenge 2023 Participant Report (Team KuzHum)

Source: [HomeRobot Open Vocabulary Mobile Manipulation Challenge 2023 Participant Report (Team KuzHum)](<https://www.sota2.com/research/paper/68fa71f81e209131cea53d6a>)

Collection index: [llms.txt](<https://www.sota2.com/research/llms.txt>)

Data updated: 2025-10-26T02:15:27.440Z

Authors: Volodymyr Kuzma, Vladyslav Humennyy, Ruslan Partsey

Published: 2024-01-22T15:40:24.000Z

## Abstract

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.

## Recorded benchmark results

A research result applies to its stated dataset, split, metric and evaluation configuration. Compare like-for-like settings, preserve the metric's unit and direction, and distinguish paper-reported results from independent reproduction. The best result recorded here is not a claim of exhaustive, current global coverage.

## Original sources and implementation

[Original paper](<https://arxiv.org/abs/2401.12048>)

[PDF](<https://arxiv.org/pdf/2401.12048.pdf>)