Bioinspired vision processing for autonomous terrestrial locomotion

用于自主地面运动的仿生视觉处理

基本信息

批准号：
EP/J012025/1
负责人：
J Burn
金额：
$ 69.92万
依托单位：
University of Bristol
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2012
资助国家：
英国
起止时间：
2012 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FJ012025%2F1
关键词：
Bioinspired vision processing autonomous terrestrial

项目摘要

Land vehicles have been designed almost exclusively to use wheels whereas terrestrial animals almost exclusively use legs for locomotion. Wheeled systems can be fast and efficient on hard flat ground; leg based systems are more versatile and efficient on natural terrain. As we move towards a future of autonomous systems operating beyond the extent of the road network and on other planets it is likely that development of robust artificial leg-based locomotion will become increasingly important.At present, several limits of technology prevent the emergence of autonomous legged systems with biocomparable performance. Even if a system was to emerge that could walk, run, leap, and turn without falling over, the technology does not exist safely to guide it through complex terrain using vision. Typically research into using vision for autonomous locomotion is undertaken using available vehicle technology - suggesting that the emergence of high-performance, vision-guided legged systems might occur at some time following the emergence of a basic high performance legged vehicle platform. In a novel approach we will expedite the development of a vision control architecture for locomotion over complex terrain by using human subjects as high performance vehicle platforms.The visual scene captured using a head mounted camera will be processed to identify terrain characteristics known to be important for control of locomotion. A map of the terrain synthesised in 3D virtual space and updated in real-time is presented to the human using a virtual reality headset. The overall outcome measure will be the locomotion performance achieved by the humans using the system compared to that with no vision information available and with normal vision.There are many benefits of this approach: it will allow us to investigate how humans modulate gait paramters and limb mechanics to compensate for partial or unreliable inforamtion about the environment. It will provide insight into the integration of feedforward and feedback control of locomotion. It will allow us to determine the locomotion performance that is possible from a given amount and quality of visually derived information given a highly developed locomotor platform and thus to understand how these two components of a high performance locomotor sytem combine to determine overall performance.The basic principles and technologies establilsed during this project will be applicable to any land vehicle whether based on wheels or legs. Additionally, the processing of visual information for locomotion control is a special case of the more generalised task to search the ground for an object or visual feature. The technology developed in this project may be translated to other applications in which visually-guided autonomous function is required.

陆地车辆几乎专门设计为使用轮子，而陆地动物几乎专门使用腿来运动。轮式系统可以在坚硬的平坦地面上快速高效地行驶；基于腿部的系统在自然地形上更加通用和高效。随着我们走向自主系统在道路网络范围之外和其他星球上运行的未来，开发强大的基于人工腿的运动可能会变得越来越重要。目前，技术的一些限制阻碍了自主系统的出现具有生物可比性能的腿式系统。即使出现了一种可以行走、奔跑、跳跃和转弯而不会摔倒的系统，也无法使用视觉安全地引导其穿过复杂的地形。通常，使用视觉进行自主运动的研究是利用现有的车辆技术进行的 - 这表明高性能、视觉引导的腿式系统的出现可能会在基本的高性能腿式车辆平台出现之后的某个时间出现。在一种新颖的方法中，我们将利用人体作为高性能车辆平台，加快开发用于复杂地形上运动的视觉控制架构。使用头戴式摄像机捕获的视觉场景将被处理，以识别已知的重要地形特征。控制运动。使用虚拟现实耳机向人类呈现在 3D 虚拟空间中合成并实时更新的地形地图。总体结果测量将是使用该系统的人类与没有可用视觉信息和正常视力的情况相比所实现的运动性能。这种方法有很多好处：它将使我们能够研究人类如何调节步态参数和肢体补偿有关环境的部分或不可靠信息的机制。它将提供对运动前馈和反馈控制集成的深入了解。它将使我们能够根据给定高度发达的运动平台的给定数量和质量的视觉衍生信息来确定可能的运动性能，从而了解高性能运动系统的这两个组件如何结合起来确定整体性能。该项目期间建立的原理和技术将适用于任何陆地车辆，无论是基于轮子还是基于腿。此外，用于运动控制的视觉信息处理是在地面上搜索物体或视觉特征的更广义任务的特例。该项目开发的技术可以转化为需要视觉引导自主功能的其他应用。