Multi-robot platforms are playing an increasingly important role in warehouse automation for efficient goods transport. This paper proposes a novel customization of a multi-robot system, called Tactile Mobile Manipulators (TacMMs). Each TacMM integrates a soft optical tactile sensor and a mobile robot with a load-lifting mechanism, enabling cooperative transportation in tasks requiring coordinated physical interaction. More specifically, we mount the TacTip (biomimetic optical tactile sensor) on the Distributed Organisation and Transport System (DOTS) mobile robot. The tactile information then helps the mobile robots adjust the relative robot-object pose, thereby increasing the efficiency of load-lifting tasks. This study compares the performance of using two TacMMs with tactile perception with traditional vision-based pose adjustment for load-lifting. The results show that the average success rate of the TacMMs (66%) is improved over a purely visual-based method (34%), with a larger improvement when the mass of the load was non-uniformly distributed. Although this initial study considers two TacMMs, we expect the benefits of tactile perception to extend to multiple mobile robots. Website: https://sites.google.com/view/tacmms

翻译：多机器人平台在高效货物运输的仓库自动化中正扮演着越来越重要的角色。本文提出了一种新颖的多机器人系统定制方案，称为触觉移动机械手（TacMMs）。每个TacMM集成了一个软体光学触觉传感器和一个带有举升机构的移动机器人，能够在需要协调物理交互的任务中实现协同运输。具体而言，我们将TacTip（仿生光学触觉传感器）安装在分布式组织与运输系统（DOTS）移动机器人上。随后，触觉信息帮助移动机器人调整机器人与物体之间的相对位姿，从而提升举升任务的效率。本研究比较了使用两个TacMMs并辅以触觉感知与基于视觉的传统位姿调整方法在举升任务中的性能。结果表明，TacMMs的平均成功率（66%）相较于纯视觉方法（34%）有所提高，当负载质量非均匀分布时，提升幅度更大。尽管这项初步研究仅涉及两个TacMMs，但我们预期触觉感知的优势将扩展至多个移动机器人。网站：https://sites.google.com/view/tacmms