Risk-Aware Motion Planning for Autonomous Vehicles: Probabilistic Risk Metrics in Sampling-Based MPC
Direct Sensor Integration for Optimization Fabrics
Caspar van Venrooij
Learning of Costs for Socially Compliant Autonomous Navigation
Fleet Design for On-Demand Last-Mile Logistics
Learning Cartesian Trajectory Following
Self-organised multi-robot goal identification and allocation
3D Semantic Labeling In Dynamic Environments
Paul van Houtum
Vehicle Lane-Change Prediction in Highways for Safety Assessment
Dynamic Retail Vehicle Routing Problems as a Markov Decision Process
Learning Online to Improve Collision Avoidance Performance
Attention-based efficiently coordinated motion planning
Alvaro Serra Gomez
Socially compliant motion planning for autonomous vehicles
Dr. J. Alonso-Mora
Elastic Roadmaps In The Context Of Dynamic Narrow Passages
Risk-aware motion planning for multi-robot systems
Students interested in a MSc project should contact the direct supervisor and provide the following information:
- Why are you interested in this project? What would you like to achieve?
- What is your experience relevant to this project? This could be past projects, past courses; theoretical knowledge or practical experience, related to constrained optimization, planning and/or robotics.
- When would you like to start and which courses will you have left by then?
- Is your motivation to do algorithmic work or applied research?
- Your transcript of record with past courses, including which master & track you are following.
- Available day/times to meet within one/two weeks.