Masters Thesis student

Job description

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future? If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match. 

Integrating Ground Speed Radars and IMU for Ego-Motion Estimation

Background

Effective vehicle stability control systems and energy-efficient driving strategies can only be achieved by accurate vehicle motion estimation. Existing methods, which primarily rely on wheel speed sensors and inertial measurements, present various inherent limitations. As a result, there is an increasing interest in developing new technologies to address these limitations. 

Ground speed radars provide valuable information about vehicle’s motion with respect to the road surface through Doppler velocity measurements. Previous studies have demonstrated that ego-motion can be accurately estimated using Doppler velocity measurements collected by these radars, e.g., [1]. Inertial measurement units (IMUs), which measure specific forces and angular velocities via embedded accelerometers and gyroscopes, have been widely used to estimate the motion of an object relative to an inertial frame. 

Radars and IMUs offer certain benefits and drawbacks. By utilizing IMU measurements, ego-motion can be estimated at frequencies ranging from 100 Hz to several kHz, due to high output date rate of IMUs. Furthermore, this approach is insensitive to environmental factors like precipitation and mud. However, the main limitation of inertial motion estimation is that its accuracy degrades over time due to drift. Additionally, it requires to be initialized from an external source as it cannot directly measure the translational velocities. In contrast, ground speed radars are not subject to drift over time since they can directly acquire relative velocity of the vehicle with respect to the environment. However, the data output rate of radars is relatively low, typically around 20-30 Hz. The measurements also exhibit a comparably high time delay due to low-level signal processing performed in the radar. Moreover, the quality of the measurements can be affected by the environmental conditions such as water splashes, etc.  

Building on these observations, the first objective of this study is to achieve an accurate and reliable ego-motion estimation by integrating the radar and IMU sensors. The aim is to obtain an integrated solution that retains the strengths of each sensor while eliminating the drawbacks. The resulting integrated solution is expected to improve performance in terms of accuracy, output rate, and robustness against outlier measurements caused by environmental factors.  

 
Another key consideration for ensuring safe and efficient driving is a good understanding of the road characteristics, including slope and bank angles. The vehicle's roll and pitch angles relative to the road surface can be estimated using Doppler velocity and/or range measurements from radars. In contrast, IMU allows for estimating the roll and pitch angles of the vehicle's body relative to the inertial frame. In this regard, the second objective of this work is to estimate the road slope and bank angles by proper integration of these two information sources.  

Objectives

The objectives of the master's thesis are as follows: 

 

·  To construct a mathematical model of the ground speed radar and the IMU to simulate realistic measurements. 
·  To develop algorithms that process radial velocity and inertial measurements to jointly estimate ego-motion, road slope and bank angles.  
·  To evaluate the sensitivity of the estimation performance with regard to the sensor imperfections, for example, bias, random noise and scaling errors. 
·  To assess the performance of the developed methods on simulated measurements. 
·  [Stretched] To assess the performance of the developed methods on real sensor measurements. 

The thesis work will require signal processing, control theory and vehicle dynamics. Interest in mathematical modeling seen as a benefit. The work will be carried out at Volvo Group Trucks Technology. The thesis is recommended for two students with control analysis profile with good mathematical skills. Thesis start: Jan 2025. 

 

Contact person: 

Murat Kumru – Volvo GTT 

tel: +46 76 553 70 05 

mail: murat.kumru@volvo.com 
 

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Who we are and what we believe in 
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Applying to this job offers you the opportunity to join Volvo Group . Every day, across the globe, our trucks, buses, engines, construction equipment, financial services, and solutions make modern life possible. We are almost 100,000 people empowered to shape the future landscape of efficient, safe and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents with sharp minds and passion across the group’s leading brands and entities. 

 

Group Trucks Technology are seeking talents to help design sustainable transportation solutions for the future. As part of our team, you’ll help us by engineering exciting next-gen technologies and contribute to projects that determine new, sustainable solutions. Bring your love of developing systems, working collaboratively, and your advanced skills to a place where you can make an impact. Join our design shift that leaves society in good shape for the next generation.

Job Category:  Technology Engineering

Organization:  Group Trucks Technology

Travel Required:  No Travel Required

Requisition ID:  14589