At VTSU Randolph we have had a ski hill since around 1939. The original rope tow was installed in 1960 and replaced in 2011. It operates under purely natural snow conditions and is open to all VTSU Randolph community.
The current initiative targets adding automated snow grooming capability to the ski hill with the first project by the 2024 mechanical class capstone having developed a proof of concept chassis from snowmobile tracks. This proof of concept is shown in the second image on the right.
This project is Amelia Vlahogiannis, Luke Williams, and I's senior project.
The objective of this project is to design and implement an automated control system for handling drive, navigation and safety as well as supporting future expansion.
Requirements:
Self & Situational Awareness (Replacing the human’s senses)
Operation Modes:
Manual (Remote Control)
Automatic Drive Control (Replacing the human)
Grooming path navigation
Emergency decision making
Safety
Mechanisms for Machine & Technician Safety
Guards & Indicators for Bystander Protection
Emergency Break on Electrical Loss
Design Considerations
Must Be Weatherproof
Must Be Expandable
This project started in late November (with a pause during holiday break) and is currently active and set to be completed by May, this page may be updated throughout that time but will definitely be updated after the project is completed.
This page was last updated 4/23/26
On April 18th, the VTSU Randolph campus held its Homecoming & Community Expo day with associates and senior projects displayed for visitors, alumni, and administrators. Below is the poster we created for the project display.
Below are two images, the first being our draft block diagram and the second being our division of responsibilities. These are not finalized diagrams and may receive updates throughout the project.
Draft block diagram of the solution, is currently revision 1 and could continue see updates throughout the project. The first main change made was condensing the operation and sensor controllers into a single controller.
Division of responsibilities diagram used for determining which requirements fall on which member of the team.
Safety and emergency decisions are made using data collected by the sensor subsystem, which is broken into two parts: system monitoring, obstacle detection.
The system monitoring part identifies and estimates the state of the system for use in decision making. The three datasets collected are from the motor drivers, interior temperature thermocouple, and from a hall effect current sensor. The current data is used to estimate the battery charge using an integral of the current (charge and discharge) measured over time.
The diagram above is a simple diagram representing how components within the system are connected for system monitoring.
On 2/18 & 2/19 the thermal and current sensing proof of concepts were demonstrated, a video of the demo is below. The demo is from revision 2 which used a lowside current shunt resistor instead of a hall effect current sensor as well as only integrated the discharging, and not the charging.
The obstacle detection system concept uses ultrasonic sensors to identify obstacles and infrared (IR) motion sensors to identify whether the obstacles are humans (or other animals). The identification of a human/animal compared to a static obstacle is important, as animals may move to avoid the snow groomer in the same direction the snow groomer moves to avoid the animal. The easiest way to visualize this is when two people walk towards each other in a hallway and both move back and forth trying to avoid each other in the same directions until hopefully someone doesn't allowing the paths to not collide.
After testing it was concluded the IR sensors were sensitive to vibration caused by the vehicle, the two solutions to resolve this that are being considered are validating their data with the obstacle sensors and/or use IR sensors which are designed for mobile use, which will require further research. After the ultrasonic sensor testing was completed, it was concluded that ultrasonic sensors cannot reliably detect humans, likely because clothing absorbs sound waves. Because of this issue, if the obstacle sensors were to validate IR data, a different technology would have to be used.
Below is a video of the obstacle detection demo, for the reasons shown above the detection technology will be changing either in part or entirely. To ensure the operational control system can remain the same, the sensor data processing will be required to process into a consistent "data packet" to be used by the operational control system acting as an abstraction layer.
Due to the issues discussed, the final demo for our automation system will use only ultrasonic sensors for decision making while alternative routes are discussed for detecting humans.
The final presentation will be on 5/4/26 with demos occurring throughout that week.
The expected deliverables are:
Operation System (Drive & Decision Control):
Implemented hardware & software
Provided Code
GPS navigation:
Including path generation and following
Implemented hardware & software
Provided code
System Monitoring: current & temperature sensing
Implemented hardware & software
Provided code
Obstacle Detection:
Finalized abstraction interface
Ultrasonic obstacle detection array
Implemented hardware & software
Provided code, concepts, and research
Safety:
Drive indicator lights
Safety beacon
Mechanical guards
Electrical loss emergency break