Thesis project: Reinforcement Learning (RL) for Autonomous Forklift Testing
Core
Develop and evaluate a reinforcement learning approach to automatically generate challenging test scenarios for autonomous forklift software to discover failures and edge cases.
Role type
Master Thesis Researcher (Reinforcement Learning for Autonomous Systems Testing)
Builds
Simulation-based test scenarios and failure discovery pipelines for autonomous forklifts
Domain
Robotics / Autonomous Systems / Machine Learning
Deliverable
research
Required skills
Reinforcement learning, Machine learning, Simulation, Programming, Software testing
Preferred skills
Autonomous systems, Optimization, Mechanical knowledge, Electrical knowledge
Responsibilities
Develop RL agents for scenario generation, Evaluate test coverage and failure discovery rates, Compare RL approaches with random testing and optimization methods, Validate simulation findings on physical autonomous trucks
Seniority
Master Thesis Researcher
