Autonomous Obstacle Avoidance with Nano-Drones and Novel Depth Sensors

Overview

Status: Available

• Type: Master Thesis, Semester Project
• Professor: Prof. Dr. L. Benini
• Supervisors:
  • Vlad Niculescu: vladn@iis.ee.ethz.ch

Project Description

thumb|center|800px| Classical ranging vs Concurrent ranging

Character

• 30% Literature and algorithm development
• 30% FreeRTOS C programming (STM32 Platform)
• 40% In-field evaluation and testing

Prerequisites

• Strong interest in embedded systems
• Experience with data acquisition and analysis
• Experience with low-level C programming

References

[1] Corbalán, Pablo, and Gian Pietro Picco. "Ultra-wideband concurrent ranging." ACM Transactions on Sensor Networks (TOSN) 16.4 (2020): 1-41.