Design Safe Navigation Behavior for a Hospital Delivery Robot
Overview
What this challenge is about.
Classify hospital corridor social contexts, switch robot driving modes, and evaluate in Gazebo simulation. Earn a verifiable certificate.
The scenario
The startup (~140 staff) sells per-robot subscriptions to hospital systems in Germany, Austria, and the Netherlands; perceived intrusiveness is the top reason pilots fail to convert.
The Brief
What you'll do, and what you'll demonstrate.
Make the delivery robot behave socially in tight hospital corridors without crippling its delivery throughput.
Earning criteria — what you'll demonstrate
- Design context-aware motion policies around humans
- Evaluate social-comfort metrics in simulation with real traces
- Reason about safety/throughput trade-offs in human-robot interaction
- Translate research metrics into a deployable policy spec
Program Fit
Where this fits in your program.
Sharpens the same skills your degree expects you to demonstrate.
Human-Robot Interaction
Master · Applied Ai
Strong alignment
This challenge maps to Human-Robot Interaction at the Master level. It sharpens the same practical skills your coursework expects — but in a real industry context with actual constraints and deliverables.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
- Human Aware Navigation
Apply human aware navigation to solve real industry problems and demonstrate production-level capability.
- Ros2
Apply ros2 to solve real industry problems and demonstrate production-level capability.
- Motion Planning
Apply motion planning to solve real industry problems and demonstrate production-level capability.
- Simulation Evaluation
Apply simulation evaluation to solve real industry problems and demonstrate production-level capability.
- Social Robotics
Apply social robotics to solve real industry problems and demonstrate production-level capability.
- Policy Design
Apply policy design to solve real industry problems and demonstrate production-level capability.
Careers
Career paths this challenge builds toward
Completing this challenge demonstrates skills that transfer directly to these roles:
AI Engineer
Shipping a human-aware policy on top of a real robotics stack with simulation evidence is the day-one work of AI engineers at any service-robotics company.
This challenge sharpens
- human-aware-navigation
- ros2
- policy-design
Machine Learning Engineer
Designing the context classifier and switching policy mirrors the MLE's job of taking research signals into a production decision boundary.
This challenge sharpens
- policy-design
- simulation-evaluation
- motion-planning
Research Scientist
Evaluating social-comfort metrics against a baseline on real traces is a credible early research-scientist project.
This challenge sharpens
- simulation-evaluation
- social-robotics
- human-aware-navigation