Brains on Board: Neuromorphic Control of Flying Robots

如果我们能设计一个具有蜜蜂导航和学习能力的自主飞行机器人会怎样？这样一个计算和节能的自主机器人将代表机器人技术的一个飞跃，而这正是“Brains on Board”项目的目标。移动的机器人的自主控制需要对环境和感知的不确定性具有鲁棒性，并具有处理新环境和场景的灵活性。动物通过具有灵活的大脑来解决这些问题，这些大脑能够在无人监督的情况下进行模式检测和学习。即使是像蜜蜂这样的“小”脑动物，也表现出复杂的学习和导航能力，使用非常有效的大脑，只有100万个神经元，比人脑少10万倍。至关重要的是，这些迷你大脑仍然支持高水平的多任务处理，并且在个人的一生中，它们能够适应全新的场景;这与典型的控制工程解决方案形成鲜明对比。该项目将融合计算和实验神经科学，开发一种突破性的新型高效“机载大脑"机器人控制器，能够在强大而轻便的通用图形处理单元硬件上运行时表现出自适应行为，现在正在出现移动的设备市场。这将通过飞行机器人的自主和自适应控制来证明，使用蜜蜂神经回路的机载计算模拟;这是一项前所未有的成就，代表了机器人技术的一步变化。

What if we could design an autonomous flying robot with the navigational and learning abilities of a honeybee? Such a computationally and energy-efficient autonomous robot would represent a step-change in robotics technology, and is precisely what the 'Brains on Board' project aims to achieve. Autonomous control of mobile robots requires robustness to environmental and sensory uncertainty, and the flexibility to deal with novel environments and scenarios. Animals solve these problems through having flexible brains capable of unsupervised pattern detection and learning. Even 'small'-brained animals like bees exhibit sophisticated learning and navigation abilities using very efficient brains of only up to 1 million neurons, 100,000 times fewer than in a human brain. Crucially, these mini-brains nevertheless support high levels of multi-tasking and they are adaptable, within the lifetime of an individual, to completely novel scenarios; this is in marked contrast to typical control engineering solutions. This project will fuse computational and experimental neuroscience to develop a ground-breaking new class of highly efficient 'brain on board' robot controllers, able to exhibit adaptive behaviour while running on powerful yet lightweight General-Purpose Graphics Processing Unit hardware, now emerging for the mobile devices market. This will be demonstrated via autonomous and adaptive control of a flying robot, using an on-board computational simulation of the bee's neural circuits; an unprecedented achievement representing a step-change in robotics technology.