Collaborative Localization with Ultra Wide Bands for Air and Space

This ambitious project merges two cutting-edge research areas to create a comprehensive system for multi-UAV collaborative localization and GPS-denied navigation, specifically targeting challenging environments such as urban areas with limited GPS access and lunar lava tubes where GPS-like signals are entirely unavailable. The project spans multiple stages, from system design to algorithm development, testing, and real-world validation. 

In Stage 1, the objective is to design and implement a system where multiple UAVs collaborate to achieve precise localization in environments with varying signal availability by using fusion of GPS and UWB (Ultra-Wideband) sensors, thus creating a robust system that can switch between relative and absolute positioning depending on signal availability. We will test various formation patterns and navigation tasks in both indoor and outdoor spaces, ensuring the system's reliability across different scenarios. 

In the second phase of the project, we will focus on developing a navigation system combining UWB and visual-inertial odometry for exploring GPS-denied environments like lunar lava tubes. We will develop advanced algorithms to fuse UWB ranging data with visual-inertial odometry, providing continuous and accurate navigation data. We will also design a prototype test bed, equipping a ground rover platform with the necessary sensors and technologies to validate the navigation system in a controlled environment.

Name of research group, project, or lab
Prof. Mohanty's Research Group
Why join this research group or lab?

Research in this lab directly addresses critical challenges in robotics, including improving navigation in uncharted environments, enhancing sensor fusion techniques, and developing robust autonomous systems. These applications extend beyond space exploration to fields like autonomous vehicles, drones, and smartphones. Key student outcomes are:

  • Students in the lab will emerge with a broad and valuable skill set, having collaborated across robotics, aerospace engineering, computer vision, and AI. 
  • Students will gain hands-on experience with cutting-edge robotics platforms, advanced sensors, and powerful computational tools, and exposure to advanced programming, machine learning, deep learning, sensor fusion, and hardware integration. 
  • Students will be equipped to develop novel solutions to complex robotics challenges by using creative thinking and engineering prototyping. 
  • Students will gain the opportunity to collaborate with either industry or government organizations on impactful projects, leading to real-world applications.
Logistics Information:
Project categories
Computer Science
Engineering
Artificial Intelligence
Robotics
Student ranks applicable
Sophomore
Junior
Senior
Student qualifications

This project is multi-faceted and welcomes students with a variety of skills. You don’t need to have expertise in all areas to contribute meaningfully to the project.

Proficiency in creating simulation environments and designing prototype systems for testing and validation would be highly ideal. Students with strong skills in developing and implementing algorithms for sensor fusion, SLAM, and collision avoidance are also encouraged to apply. Knowledge of UWB-based positioning systems and their integration with other navigation technologies would be a plus. 

Interested students can directly email Prof. Mohanty with their CV/Resume and their responses to these questions:

  1. Explain how you would tackle the challenge of navigating in GPS-denied environments, such as lunar lava tubes. What techniques would you consider, and how would you ensure the robustness and accuracy of the navigation system?
  2. How would you approach designing a system that can switch between relative and absolute positioning in environments with varying signal availability?
  3. Describe a previous experience where you were involved in designing or prototyping a complex system. What were the key challenges you faced, and how did you overcome them? How would you apply these lessons to designing and testing the navigation system in this project?
Time commitment
Fall - Part Time
Spring - Part Time
Summer - Full Time
Compensation
Academic Credit
Paid Research
Number of openings
3
Techniques learned

Sensor fusion, multi-agent coordination, indoor and outdoor testing of ground robots and UAVs, visual-inertial odometry, UWB ranging and data logging, prototype design and testing, system validation

Project start
Fall 2024
Contact Information:
Mentor
admohanty@hmc.edu
Principal investigator
Name of project director or principal investigator
Dr. Adyasha Mohanty
Email address of project director or principal investigator
admohanty@g.hmc.edu
3 sp. | 5 appl.
Hours per week
Fall - Part Time (+2)
Fall - Part TimeSpring - Part TimeSummer - Full Time
Project categories
Robotics (+3)
Computer ScienceEngineeringArtificial IntelligenceRobotics