Biologically inspired transportation: a distributed intelligent conveyor

并联机械手是由简单的单个执行器组成的巨大阵列，具有小的功率密度，它们共同运输和定位质量比单个执行器产生的力大得多的物体。这一设计的灵感来自纤毛的生物现象，纤毛是细胞表面的小毛发结构，可以感知局部特性，如用于视觉的杆状光感受器或用于嗅觉的嗅觉神经元，或者可以以协调的波动作在其表面移动液体，如在气管和肾脏。在微执行器的模拟阵列中使用这些功能将产生一种并行智能操作传送器，能够感知对象属性，将它们向不同方向移动，并根据对象属性有效地对对象进行分类。重要的是，执行器阵列将能够将关于对象的本地信息传递到阵列的其他部分，以实现协调操作。并行智能操作在智能机器人、计算机科学和智能制造系统中发挥着越来越重要的作用。分布式操作系统的显著优势是任务的灵活性(可以动态重新编程以执行另一个任务)；大规模并行性(可以同时处理多个不同的对象，机械手的不同部分可以同时执行不同的任务)；容错(单个执行器中的故障不会限制系统的整体性能，因此可以保持系统的运行)；自主性；以及同时和独立处理对象的能力。本项目的总体目标是构建一个智能自主式大规模并行机械手，用于分布式传感、识别、分析、分类、运输和操作轻量对象。机械手的控制系统将采用反应扩散计算的范式，即通过在非线性介质中传播波形来进行信息处理和计算。我们将利用进化计算和机器学习来开发基于非线性介质的控制的新原理和实现，并引入一系列分布式感知(对象属性如形状)、过滤(根据共同特征对不同对象进行分类)、定向(确保对象朝向正确的方向)、这种机械手系统不仅在进化算法、反应扩散计算和智能机器人系统的进步方面对学术界产生潜在的影响，而且在工业领域也有现成的应用领域，如高科技制造，使先进的传感器网络能够控制机械部件的动力学，纳米设备的自动化组装，以及医疗应用，如假肢和计算机控制的植入物。

A parallel manipulator is a massive array of simple individual actuators with a small power density that collectively transport and position objects with masses considerably higher than the force generated by a single actuator alone. This design is inspired by the biological phenomena of cilia, small hair-like structures on the surface of cells which can either sense local properties such as in the rod photoreceptors for vision or in olfactory neurons for smell, or can move in coordinated wave action to move liquid over their surface, as in the trachea and kidneys. Employing these capabilities in an analogous array of micro-actuators will produce a conveyor of parallel intelligent manipulation able to sense object properties, move them in different directions and effectively sort objects according to their properties. Crucially, the actuator array will be capable of communicating local information about objects to other parts of the array to enable coordinated action.Parallel intelligent manipulation plays an increasingly important role in intelligent robotics, computer science and intelligent manufacturing systems. Significant advantages of the distributed manipulating system are task flexibility (it can be dynamically reprogrammed to implement another task); massive-parallelism (it can process several different objects simultaneously, and different parts of the manipulator can perform separate tasks concurrently); fault tolerance (faults in single actuators do not restrict performance of the system as a whole, so operation of the system can be maintained); autonomy; and the ability to process objects simultaneously and independently.The overarching aim of the project is to build an intelligent autonomous massively parallel manipulator for distributed sensing, recognition, analysis, sorting, transportation and manipulation of light-weight objects. A paradigm of reaction-diffusion computing, i.e. information processing and computation by spreading wave-patterns in non-linear media, will be employed in the control system of the manipulator.Using evolutionary computation and machine learning, we will develop new principles and implementations for non-linear medium based control, and introduce a range of algorithms for distributed sensing (of object properties such as shape), filtration (sorting different objects according to common characteristics), orienting (ensure objects are facing and moving in the correct direction), positioning (moving objects into the correct path of travel on a different part of the manipulator) and shape-determined transportation of the objects.This manipulator system not only has the potential to impact upon the academic community in terms of the advancement of evolutionary algorithms, reaction-diffusion computing, and intelligent robotic systems, but also has ready application domains in industry such as high-tech manufacturing, enabling an advanced network of sensors to control dynamics of mechanical components, automation of assembly of nano-devices, and medical applications such as prostheses and computer controlled implants.