Design Safe Navigation Behavior for a Hospital Delivery Robot
Overview
What this challenge is about.
You receive a dataset of 200 anonymized hospital corridor traces (people positions over time from the robot's LIDAR) plus the current planner's parameters. Design a policy that classifies the local social context (empty corridor, single passer-by, group, narrow squeeze, queue at elevator) and switches between three driving modes (cruise, polite, defer). Implement it on top of an existing ROS 2 Nav2 stack and evaluate it in Gazebo using the logged traces as replayed pedestrians. Deliver: the policy spec, a 4-page simulation report comparing the new policy to baseline on three social-comfort metrics, and a one-page protocol for an in-hospital 2-day trial.
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.
Skills
Skills you'll demonstrate.
Each one shows up on your verified credential.
Careers
Roles this prepares you for.
Real titles. Real skill bridges. Pick the one closest to your trajectory.
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