A complete neuromorphic solution to outdoor navigation and path planning

摘要

Recent developments in neuromorphic engineering have enabled low-powered processing and sensing in robotics, leading to more efficient brain-like computation for many robotic tasks such as motion planning and navigation. However, present experiments in neuromorphic robotic systems have mostly been performed under controlled indoor settings, often with unlimited power supply. While this may be suitable for many applications, these algorithms often fail in outdoor dynamic environments that could benefit the most from the low size, weight, and power of neuromorphic devices. We present the current challenges of outdoor robotics, how current neuromorphic solutions can address these problems, our current approaches to the task, and what further needs to be achieved to create a complete neuromorphic solution to outdoor navigation and path planning.