Tactile sensors have been introduced to a wide range of robotic tasks such as robot manipulation to mimic the sense of human touch. However, there has only been a few works that integrate tactile sensing into robot navigation. This paper describes a navigation system which allows robots to operate in crowded human-dense environments and behave with socially acceptable reactions by utilizing semantic and force information collected by embedded tactile sensors, RGB-D camera and LiDAR. Compliance control is implemented based on artificial potential fields considering not only laser scan but also force reading from tactile sensors which promises a fast and reliable response to any possible collision. In contrast to cameras, LiDAR and other non-contact sensors, tactile sensors can directly interact with humans and can be used to accept social cues akin to natural human behavior under the same situation. Furthermore, leveraging semantic segmentation from vision module, the robot is able to identify and, therefore assign varying social cost to different groups of humans enabling for socially conscious path planning. At the end of this paper, the proposed control strategy was validated successfully by testing several scenarios on an omni-directional robot in real world.
翻译:将触觉感应纳入机器人导航中,本文描述了一种导航系统,允许机器人在拥挤的人类感官环境中操作,并且利用嵌入的触动感应器、RGB-D相机和激光雷达收集的语义和力学信息,以社会可接受的反应方式行事。 合规控制是根据人造潜在领域实施的,不仅考虑激光扫描,而且考虑从触摸感应快速可靠地应对任何可能的碰撞的触觉读。与照相机、激光雷达和其他非接触感应器不同,触控感应器可以直接与人类互动,并可用于接受与人类在同样情况下的自然行为类似的社会信号。此外,利用从视觉感应感应传感器、RGB-D相机和激光雷达收集的语义和力学信息,机器人能够识别并因此为不同群体分配不同的社会成本,以便能够进行有社会意识的路径规划。在本文结尾处,通过在现实世界中测试一些原型机器人,成功地验证了拟议的控制战略。