Pulling open cabinets and drawers presents many difficult technical challenges in perception (inferring articulation parameters for objects from onboard sensors), planning (producing motion plans that conform to tight task constraints), and control (making and maintaining contact while applying forces on the environment). In this work, we build an end-to-end system that enables a commodity mobile manipulator (Stretch RE2) to pull open cabinets and drawers in diverse previously unseen real world environments. We conduct 4 days of real world testing of this system spanning 31 different objects from across 13 different real world environments. Our system achieves a success rate of 61% on opening novel cabinets and drawers in unseen environments zero-shot. An analysis of the failure modes suggests that errors in perception are the most significant challenge for our system. We will open source code and models for others to replicate and build upon our system.

翻译：拉开柜子和抽屉带来了诸多技术挑战：感知方面（从机载传感器推断物体的铰接参数）、规划方面（生成符合严格任务约束的运动规划）以及控制方面（在向环境施加力的同时建立并维持接触）。在这项工作中，我们构建了一个端到端系统，使商品化移动机械手（Stretch RE2）能够在多样化且未见过的现实环境中拉开柜子和抽屉。我们对该系统进行了为期4天的现实世界测试，涉及来自13个不同现实环境的31个不同物体。我们的系统在零样本情况下打开未见环境中新型柜子和抽屉的成功率达到61%。对故障模式的分析表明，感知误差是我们系统面临的最重大挑战。我们将开源代码和模型，供他人复制和进一步发展我们的系统。