Master Thesies \"Hybrid Motion Planning\"

JobsinAustria; Wien; Vor Ort; EUR 6.100 - 7.800; Teilzeit

Benefits dieser Stelle

Meal allowance

Organic coffee

Fruit baskets

Preventive healthcare benefits

Company doctor

Flexible working hours (home office up

Zusammenfassung

AIT Austrian Institute of Technology in Vienna invites applications for a master thesis on hybrid motion planning for real-time model predictive control in robotics. You will explore combining gradient-based and sampling-based optimisation to improve trajectory generation.

Responsibilities include literature review, algorithm analysis, MATLAB implementation, simulation-based evaluation on ground vehicles, and an experimental test on a Husky platform, under expert supervision.

Qualifikationen

• Ongoing master's studies in automation & control or related field.
• Excellent knowledge in optimization.
• Excellent knowledge of MATLAB and Python.
• Strong analytical capabilities and technical understanding.
• Interest in industry-oriented applied questions.

Aufgaben

• Conduct a comprehensive literature review of motion planning methods and solvers.
• Analyse and compare existing algorithms for hybrid planning.
• Implement the selected algorithms in MATLAB.
• Evaluate the methods in simulation with ground vehicles.
• Perform an experimental evaluation on a Husky platform.
• Analyze results and derive recommendations for future research.
• Discuss results with interdisciplinary experts from mathematics, informatics, physics and control.

Kenntnisse

Optimization

Analytical thinking

Teamwork

German/English language

Ausbildung

Ongoing master's studies in automation & control

Technical mathematics

Technical Informatics

Tools

MATLAB

Python

Jobbeschreibung

The AIT Austrian Institute of Technology is Austria’s largest Research and Technology Organisation (RTO). We aim to transform scientific excellence into innovation with impact. Together with our partners, we develop technologies and solutions for a sustainable, resilient, and digitalized future, strengthening Europe’s competitiveness and technological sovereignty. Our international teams combine cutting-edge research with strong implementation expertise to create measurable value for industry and society.

Our research unit Complex Dynamical Systems located in Vienna (Argentinierstraße) at the Center for Vision, Automation & Control invites applications for a master thesis. We focus our research on modelling, simulation, analysis and optimsation and control of complex and dynamical industrial systems and processes to enhance product quality, increase flexibility, and improve resource efficiency. These methods are applied accross a broad range of industrial domains such as mechatronics, robotics, and industrial production facilities.

As part of this master’s thesis, you will investigate hybrid motion planning methods for real-time model predictive control in robotics, with a particular focus on combining gradient-based and sampling-based optimisation techniques. Motion planning enables autonomous vehicles and robots to navigate safely and efficiently in complex environments. However, nonlinear dynamics, state and actuation constraints, and environments containing multiple obstacles give rise to non-convex optimisation landscapes in which gradient-based methods may converge to local minima and fail to compute feasible trajectories. Stochastic optimisation methods, such as Model Predictive Path Integral Control (MPPI), have been developed to mitigate these limitations by improving exploration of the solution space. However, such methods can suffer from noisy solutions and slow convergence. Hybrid approaches aim to combine the fast local convergence properties of gradient-based optimal control with the global exploration capabilities of sampling-based methods.

Master Theses "Hybrid Motion Planning"

Center for Vision, Automation & Control

• Conduct a comprehensive literature review of motion planning, known solution methods and available solvers for the problems addressed above
• Analyse and compare existing algorithms
• Implement the best suited algorithms in MATLAB.
• Under the guidance of our researchers, evaluate the implemented methods in simulation using ground vehicles.
• Perform an experimental evaluation on a Huskey platform.
• Analyse, document and present the obtained results and derive recommendations for future research.
• Train scientific work and benefit from the opportunity to discuss your results and experiences with interdisciplinary experts from the fields of mathematics, informatics, physics and control and mechanical engineering.

Your qualifications as an Ingenious Partner

• Ongoing master's studies in the field of automation & control, technical mathematics, technical Informatics or a comparable technical field.
• Excellent knowledge in the field of optimization
• Excellent knowledge of MATLAB and Python.
• Excellent technical understanding & analytical capabilities
• Enjoyment of application-oriented questions of industry
• High level of commitment and team spirit
• Good knowledge of German and/or English in word and writing

What to expect

• Duration of the master’s thesis project: approximately 6 months
• Dedicated guidance and supervision from our experienced researchers, who will support you throughout your final thesis - from the initial concept to the final results.
• EUR 616,44,- - gross per month for 12 hours/week based on the collective agreement.
• Highlights of our employee benefits include meal allowance, organic coffee, tea and fruit baskets, preventive healthcare benefits and company doctor, additional days off for various life events, leisure subsidies, voucher programme, sports, cultural and socialising events, as well as flexitime models (incl. home office possibilities up to 50%).

At AIT diversity and inclusion are of great importance. This is why we strive to inspire women to join our teams in the field of technology. We welcome applications from women, who will be given preference in case of equal qualifications after taking into account all relevant facts and circumstances of all applications.