论文标题
Urobosim-机器人代理中前瞻性推理的情节模拟框架
URoboSim -- An Episodic Simulation Framework for Prospective Reasoning in Robotic Agents
论文作者
论文摘要
预期行动可能发生的事情是人类有效执行任务的基本能力。另一方面，在这方面的机器人功能非常缺乏。在使用机器学习来提高前提能力的同时，对于新型情况仍在限制。通过模拟想象的动作和这些动作的身体结果，提高机器人的假期能力的可能性。因此，我们提出了一种机器人模拟器Urobosim，它允许机器人在现实执行此任务之前执行任务作为心理模拟。我们以心理模拟的形式显示了urrobosim的能力，为机器学习生成数据以及作为真正机器人的信念状态的用法。
Anticipating what might happen as a result of an action is an essential ability humans have in order to perform tasks effectively. On the other hand, robots capabilities in this regard are quite lacking. While machine learning is used to increase the ability of prospection it is still limiting for novel situations. A possibility to improve the prospection ability of robots is through simulation of imagined motions and the physical results of these actions. Therefore, we present URoboSim, a robot simulator that allows robots to perform tasks as mental simulation before performing this task in reality. We show the capabilities of URoboSim in form of mental simulations, generating data for machine learning and the usage as belief state for a real robot.
