Mission Logs document objectives, experiments, observations, results, and next steps. Draft entries are clearly labelled because the goal is scientific traceability, not exaggerated marketing.
6
Research notes
MDX-ready
Future equations and figures
Linked
Projects and graph
Why Uncertainty Matters in Robotics
Objective
Frame uncertainty as an operational signal rather than a decorative confidence score.
Experiment
Map where uncertainty enters the robotics stack: sensing, estimation, prediction, planning, and control.
Observation
Most autonomy failures are not caused only by wrong predictions, but by systems acting as if uncertain estimates were certain.
Next step
Connect SHIELD-VIO health scores to DynNav risk-aware planning scenarios.
Result
The portfolio should expose uncertainty explicitly in every project page, demo, and metric table.
UncertaintySafetyVIO
From VIO to Risk-Aware Navigation
Objective
Show how localization confidence can become a planning input.
Experiment
Define a conceptual interface from VIO health monitoring to navigation risk cost.
Observation
A planner that ignores localization health may choose paths that are geometrically short but operationally unsafe.
Next step
Prototype a synthetic demo where rising VIO uncertainty increases path risk.
Result
Research map edge SHIELD-VIO → DynNav now represents localization-health-aware navigation.
VIONavigationRisk
Semantic Perception for Delivery Robots
Objective
Treat semantic segmentation as a navigation support module, not only a computer-vision output.
Experiment
List semantic classes that matter for sidewalk and urban delivery navigation.
Observation
The useful output is not only class accuracy; the robot needs traversability, uncertainty, and failure-case awareness.
Next step
Add placeholder-to-real demo path for semantic maps and safe local navigation overlays.
Result
The delivery robot project is connected to Perception and Navigation in the research map.
PerceptionComputer VisionNavigation
Building Research Repositories Like Lab Software
Objective
Define repository standards for research software: clear assumptions, pending metrics, and reproducible commands.
Experiment
Review project pages for claims that need to be marked as planned, synthetic, or pending.
Observation
Scientific honesty is a design feature: it helps reviewers understand what is implemented and what is future work.
Next step
Add GitHub Actions checks and per-project experiment manifests.
Result
Project pages use implementation-status tables and limitation sections.
ReproducibilitySoftwareSLAM
Simulation as a Tool for Robotics Research
Objective
Use simulation to test edge cases while real robot data and benchmarks are pending.
Experiment
Separate synthetic demos from verified experimental results across the portfolio.
Observation
Synthetic demos are valuable when clearly labelled; they become misleading only when presented as real benchmarks.
Next step
Create seeded simulation cards for navigation, VIO uncertainty, and strategy optimization.
Result
The demos page and project pages should keep synthetic, planned, and real artifacts visually distinct.
SimulationPlanningEvaluation
Communication Uncertainty in Underwater Autonomy
Objective
Extend the uncertainty theme beyond perception and localization into communication-constrained autonomy.
Experiment
Draft a mapping from channel reliability to robot decision constraints.
Observation
A communication link is another uncertain sensorimotor resource, especially in underwater systems.
Next step
Define channel metrics and avoid claims until simulation results are reproducible.
Result
OpenUWOC-AI is represented as a communication uncertainty branch of the research ecosystem.
CommunicationsUncertaintyAI
Notebook policy
Unfinished entries remain marked as Draft or Planned. Results are not presented as benchmarks until reproducible experiments, data, and metrics are available.