可变形无人车能安全完成复杂形变，适应多种任务需求。
Affine Transformable Unmanned Ground Vehicle
- 用深度神经网络设计细胞连接结构，实现自由形变
- 通过步进电机控制，使所有单元安全跟踪目标形变
- 适合需要灵活变形的复杂场景应用
本文提出一种新型仿射可变形无人地面车辆（ATUGV），可在承载多个载荷的情况下安全且激进地变形。该ATUGV为多体系统，包含可驱动的移动机器人、用于包裹机器人的动力单元、用于装载载荷的无动力单元，以及通过杆和关节连接的可变形结构。目标是使所有动力与非动力单元运动能够安全跟踪期望的仿射变换，其可分解为平移、刚体旋转和形变。为此，论文首先利用深度神经网络构建单元间连接结构，使每个单元能在变形平面内自由运动，并实现整体结构可重构形变以跟踪目标仿射变换。随后，通过嵌入动力单元的移动机器人和步进电机，调节动力与非动力单元之间的连接，设计相应控制策略，确保所有单元安全追踪目标仿射变换。所提ATUGV的功能通过硬件实验与仿真验证。
原文摘要 · Abstract (English)
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.
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