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arXiv 2407.06951cs.ROcs.LG
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RoboCAS：复杂物体排列场景下机器人操作的基准

RoboCAS: A Benchmark for Robotic Manipulation in Complex Object Arrangement Scenarios

Meituan（美团）

Liming Zheng, Feng Yan, Fanfan Liu, Chengjian Feng, Zhuoliang Kang, Lin Ma

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AI总结：

本文提出RoboCAS基准，首个专为机器人操作中复杂物体排列场景设计的基准，通过逼真仿真环境测试智能体在模糊指令下的长程规划与空间推理能力，揭示了现有基线模型的局限性。

摘要：

基础模型在使机器人执行长程通用操作任务方面具有巨大潜力。然而，现有基准中任务的简单性和环境的单一性限制了它们在复杂场景中的有效部署。为了解决这一局限性，本文提出了RoboCAS基准，这是首个专为机器人操作中复杂物体排列场景设计的基准。该基准采用灵活且简洁的脚本策略来高效收集多样化的演示数据，在高度逼真的物理仿真环境中展示了散乱、有序和堆叠的物体排列方式。它包含目标检索、障碍清除和机器人操作等复杂过程，测试智能体在模糊指令下进行长程规划以实现空间推理和预测连锁反应的能力。在多个基线模型上的大量实验揭示了它们在处理复杂物体排列场景时的局限性，凸显了在实际部署中迫切需要能够执行长程操作的智能体，并为未来研究方向提供了有价值的见解。项目网站：https://github.com/notFoundThisPerson/RoboCAS-v0。

英文摘要：

Foundation models hold significant potential for enabling robots to perform long-horizon general manipulation tasks. However, the simplicity of tasks and the uniformity of environments in existing benchmarks restrict their effective deployment in complex scenarios. To address this limitation, this paper introduces the \textit{RoboCAS} benchmark, the first benchmark specifically designed for complex object arrangement scenarios in robotic manipulation. This benchmark employs flexible and concise scripted policies to efficiently collect a diverse array of demonstrations, showcasing scattered, orderly, and stacked object arrangements within a highly realistic physical simulation environment. It includes complex processes such as target retrieval, obstacle clearance, and robot manipulation, testing agents' abilities to perform long-horizon planning for spatial reasoning and predicting chain reactions under ambiguous instructions. Extensive experiments on multiple baseline models reveal their limitations in managing complex object arrangement scenarios, underscoring the urgent need for intelligent agents capable of performing long-horizon operations in practical deployments and providing valuable insights for future research directions. Project website: \url{https://github.com/notFoundThisPerson/RoboCAS-v0}.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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