Design of an Intent Recognition System for Dynamic, Rapid Motions in Unstructured Environments
Design of an Intent Recognition System for Dynamic, Rapid Motions in Unstructured Environments
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DOI：
10.1115/1.4051140
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通讯作者：
Pooja Moolchandani;A. Mazumdar;Aaron J. Young
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作者：
Pooja Moolchandani;A. Mazumdar;Aaron J. Young
在这项研究中，我们开发了一个离线的、分层的意图识别系统，用于推断操作员在非结构化环境中操作时的运动意图的时间和方向。对机器人代理的需求越来越大，以帮助这些动态、快速的运动，这些运动不断发展，需要快速、准确地估计用户的行进方向。实验在运动捕捉空间进行，六名受试者在八个方向上进行威胁回避，他们的机械和神经肌肉信号被记录下来，用于我们的意图识别系统(XGBoost)。与目前的分析方法相比，我们的系统表现出了优越的性能，在移动过程中更快地估计了移动的方向，并减少了11.6度的误差。结果显示，我们还可以预测运动的开始时间比实际运动早100毫秒，从而允许任何物理系统启动。使用三轴运动数据，我们的方向估计的最佳性能为8.8度，或360度行程范围的2.4%。其他传感器及其组合的性能表明，存在获得低估计误差的额外可能性。这些发现很有希望，因为它们可以用来设计一种可穿戴机器人，旨在帮助用户在面临威胁的环境中进行动态运动。
In this study, we developed an offline, hierarchical intent recognition system for inferring the timing and direction of motion intent of a human operator when operating in an unstructured environment. There has been an increasing demand for robot agents to assist in these dynamic, rapid motions that are constantly evolving and require quick, accurate estimation of a user’s direction of travel. An experiment was conducted in a motion capture space with six subjects performing threat evasion in eight directions, and their mechanical and neuromuscular signals were recorded for use in our intent recognition system (XGBoost). Investigated against current, analytical methods, our system demonstrated superior performance with quicker direction of travel estimation occurring 140 ms earlier in the movement and a 11.6 deg reduction of error. The results showed that we could also predict the start of the movement 100 ms prior to the actual, thus allowing any physical systems to start up. Our direction estimation had an optimal performance of 8.8 deg, or 2.4% of the 360 deg range of travel, using three-axis kinetic data. The performance of other sensors and their combinations indicate that there are additional possibilities to obtain low estimation error. These findings are promising as they can be used to inform the design of a wearable robot aimed at assisting users in dynamic motions, while in environments with oncoming threats.