We present a deep-dive into a real-world robotic learning system that, in
previous work, was shown to be capable of hundreds of table tennis rallies with
a human and has the ability to precisely return the ball to desired targets.
This system puts together a highly optimized perception subsystem, a high-speed
low-latency robot controller, a simulation paradigm that can prevent damage in
the real world and also train policies for zero-shot transfer, and automated
real world environment resets that enable autonomous training and evaluation on
physical robots. We complement a complete system description, including
numerous design decisions that are typically not widely disseminated, with a
collection of studies that clarify the importance of mitigating various sources
of latency, accounting for training and deployment distribution shifts,
robustness of the perception system, sensitivity to policy hyper-parameters,
and choice of action space. A video demonstrating the components of the system
and details of experimental results can be found at
this https URL

该篇论文深入研究了一个真实世界的机器人学习系统，该系统能够和人类进行数百次乒乓球对打，并能够精确地将球返回到指定目标。论文提供了完整的系统描述，包括通常不广泛传播的设计决策，并附上一系列研究，澄清了减轻潜在延迟来源的重要性，考虑训练和部署分布变化的影响，感知系统的稳健性，策略超参数的敏感性以及行动空间的选择。

机器人乒乓球：高速学习系统案例研究

Robotic Table Tennis: A Case Study into a High Speed Learning System

Popular test oracles for the perception subsystem of driving automation
systems identify true-positive (TP), false-positive (FP), and false-negative
(FN) objects. Oracle transparency is needed for comparing test results and for
safety cases. To date, there exists a common notion of TPs, FPs, and FNs in the
field, but apparently no published way to comprehensively define their oracles.
Therefore, this paper provides a checklist of functional aspects and
implementation details that affect the oracle behavior. Besides labeling
policies of the test set, we cover fields of view, occlusion handling,
safety-relevant areas, matching criteria, temporal and probabilistic issues,
and further aspects. Even though our checklist can hardly be formalized, it can
help practitioners maximize the transparency of their oracles, which, in turn,
makes statements on object perception more reliable and comparable.

一篇研究文章阐述了关于驾驶自动化系统感知子系统的常用测试神谕，包括真正阳性、假阳性和假阴性对象的定义和行为，提供了一份检查表，详细描述了影响神谕行为的功能方面和实现细节，以及最大化神谕的透明度并使其准确可靠的实践方法。