Learning from demonstration (LfD) has the potential to greatly increase the applicability of robotic manipulators in modern industrial applications. Recent progress in LfD methods have put more emphasis in learning robustness than in guiding the demonstration itself in order to improve robustness. The latter is particularly important to consider when the target system reproducing the motion is structurally different to the demonstration system, as some demonstrated motions may not be reproducible. In light of this, this paper introduces a new guided learning from demonstration paradigm where an interactive graphical user interface (GUI) guides the user during demonstration, preventing them from demonstrating non-reproducible motions. The key aspect of our approach is determining the space of reproducible motions based on a motion planning framework which finds regions in the task space where trajectories are guaranteed to be of bounded length. We evaluate our method on two different setups with a six-degree-of-freedom (DOF) UR5 as the target system. First our method is validated using a seven-DOF Sawyer as the demonstration system. Then an extensive user study is carried out where several participants are asked to demonstrate, with and without guidance, a mock weld task using a hand held tool tracked by a VICON system. With guidance users were able to always carry out the task successfully in comparison to only 44% of the time without guidance.
翻译:从演示中学习(LfD)有可能极大地提高机器人操纵者在现代工业应用中的应用性。LfD方法最近的进展在学习强健性方面比在指导演示本身以提高强力性方面更加强调学习强健性,后者特别重要,因为如果目标系统复制该运动,其结构与示范系统不同,因为一些示范性动议可能无法再复制。鉴于此,本文件引入了一种新的从示范模式中进行的指导性学习,即交互式图形用户界面(GUI)在演示期间指导用户,防止他们展示不可复制的动作。我们方法的关键方面是根据运动规划框架确定可复制动作的空间,即发现任务空间中的区域,保证轨道与演示系统有密切的联系。我们评估了我们使用六度自由度(DOF) UR5作为目标系统的不同设置的方法。我们首先使用7度DF Sawy(GUI)作为演示系统的验证方法,防止他们展示不可复制的动作。然后进行广泛的用户研究,请若干参与者在不经过指导的情况下,以44度指导的方式,在任务空间空间空间中进行演示,并始终对44号用户进行跟踪。我们的工作指导。