This paper develops the proof of concept for a novel affine transformable unmanned ground vehicle (ATUGV) with the capability of safe and aggressive deformation while carrying multiple payloads. The ATUGV is a multi-body system with mobile robots that can be used to power the ATUGV morphable motion, powered cells to enclose the mobile robots, unpowered cells to contain payloads, and a deformable structure to integrate cells through bars and joints. The objective is that all powered and unpowered cells motion can safely track a desired affine transformation, where an affine transformation can be decomposed into translation, rigid body rotation, and deformation. To this end, the paper first uses a deep neural network to structure cell interconnection in such a way that every cell can freely move over the deformation plane, and the entire structure can reconfigurably deform to track a desired affine transformation. Then, the mobile robots, contained by the powered cells and stepper motors, regulating the connections of the powered and unpowered cells, design the proper controls so that all cells safely track the desired affine transformation. The functionality of the proposed ATUGV is validated through hardware experimentation and simulation.

翻译：本文提出了一种新型仿射可变形无人地面载具（ATUGV）的概念验证，该载具具备在承载多组有效载荷的同时实现安全且主动形变的能力。ATUGV是一个多体系统，包含：用于驱动ATUGV可变形运动的移动机器人、用于封装移动机器人的动力单元、用于容纳有效载荷的无动力单元，以及通过连杆与关节集成各单元的可变形结构。其目标是使所有动力单元与无动力单元的运动能够安全跟踪期望的仿射变换，其中仿射变换可分解为平移、刚体旋转与形变。为此，本文首先采用深度神经网络构建单元互联结构，使得每个单元可在形变平面上自由移动，且整体结构能够通过可重构形变跟踪期望的仿射变换。随后，通过封装于动力单元内的移动机器人及步进电机调节动力单元与无动力单元的连接关系，设计相应的控制策略，使所有单元安全跟踪目标仿射变换。所提出的ATUGV功能通过硬件实验与仿真验证。