Autonomous Seed-Planting OTV
1st of 126 teams — and the lowest environmental impact
- 1st / 126
- UMD teams
- $50+
- Fasteners eliminated
- Award
- Sustainability winner
Problem
Build an over-terrain vehicle that plants seeds while autonomously traversing a randomized obstacle course — scored on performance and environmental impact.
Motivation
First-semester design competition; the team treated the sustainability scoring not as a checkbox but as the design driver.
Constraints
- Randomized obstacles — no pre-programmed path possible
- Environmental-impact scoring on materials and construction
- First-year team, one semester, fixed budget
Process
- 01
Mechanical design
Modeled the OTV in Onshape around dovetail joints and reusable material, eliminating $50+ of fasteners through design-for-manufacture.
- 02
Autonomy
Implemented embedded systems with machine-learning vision in Python and C++ to traverse the randomized obstacle field.
- 03
Propulsion & electronics
Assembled the tripod propulsion system and soldered electronics, sized through torque, power, runtime, and battery calculations.
Key decisions
Dovetail joints instead of fasteners
Why · Cut $50+ in hardware, simplified assembly, and directly drove the environmental-impact score that the design ultimately won.
Results
- ✓Selected 1st of 126 UMD teams.
- ✓Won the Sustainability Award for the lowest-environmental-impact design.
Lessons learned
- Scoring criteria are design fuel — the sustainability constraint produced the winning architecture.