论文标题
Ewarenet：情感意识到的人类意图预测和适应性的空间概况融合社会机器人导航
EWareNet: Emotion Aware Human Intent Prediction and Adaptive Spatial Profile Fusion for Social Robot Navigation
论文作者
论文摘要
我们介绍了Ewarenet，这是行人中的一种新颖的意图和情感感知的社会机器人导航算法。我们的方法可以预测步态序列的基于轨迹的行人意图，然后考虑到社会和邻近的限制，该方法被用于指导导航。我们提出了一个基于变压器的模型，该模型可用于安装在移动机器人上的商品RGB-D摄像机。我们的意图预测程序已集成到无MAP导航方案中，并且对行人运动的环境没有任何假设。我们的导航方案由一种新颖的障碍物概况表示方法组成，该方法基于行人姿势，意图和情感进行动态调整。导航方案基于一种增强学习算法，该算法除了环境配置外，还要考虑行人意图和机器人对行人意图的影响。我们在3D步态的意图预测方面优于当前最新算法。
We present EWareNet, a novel intent and affect-aware social robot navigation algorithm among pedestrians. Our approach predicts the trajectory-based pedestrian intent from gait sequence, which is then used for intent-guided navigation taking into account social and proxemic constraints. We propose a transformer-based model that works on commodity RGB-D cameras mounted onto a moving robot. Our intent prediction routine is integrated into a mapless navigation scheme and makes no assumptions about the environment of pedestrian motion. Our navigation scheme consists of a novel obstacle profile representation methodology that is dynamically adjusted based on the pedestrian pose, intent, and affect. The navigation scheme is based on a reinforcement learning algorithm that takes pedestrian intent and robot's impact on pedestrian intent into consideration, in addition to the environmental configuration. We outperform current state-of-art algorithms for intent prediction from 3D gaits.
