Bio inspired magnetic navigation finds paths without maps
Bio-Inspired Magnetic Navigation Using Gradient Descent With Rao-Blackwellized Particle Filtering
Robotics
Summary
GPS doesn’t always work, especially indoors or underground, so people use magnetic fields to help navigate. Normally, this needs detailed magnetic maps that are expensive and heavy to make. The authors show a way to navigate using magnetic signals without these maps by using a process like following a slope downhill, guided by a type of smart guessing called a Rao-Blackwellized particle filter. This method makes navigation simpler and uses less memory.
What this means in practice
- •For robotic navigation developers: Build robots that navigate indoors or underground using magnetic field gradients without relying on complex magnetic maps.
- •For drone navigation engineers: Enable drones to find their way in GPS-denied areas by following magnetic gradients estimated through particle filtering.
Authors
Zayed Herma, Andrea Vassilev, Philippe Cardin, Jean-Michel Leger
Abstract
Navigation in GPS-denied environments is commonly based on magnetic maps, which are used to correct trajectory drift and enable relocalization. However, such navigation systems suffer from a strong dependence on magnetic maps that are complex, heavy, and costly to construct. Bio-inspired magnetic navigation (BIMN) does not rely on magnetic maps, making it simpler and more frugal. In this paper, we present a gradient descent BIMN method based on the Rao-Blackwellized particle filter (RBPF) for local gradient estimation. We show that magnetic navigation can be performed without magnetic maps, as gradient descent naturally attracts the system toward the destination, resulting in a simple and memory-efficient approach.