Project Overview
This research project investigates how pit vipers leverage both infrared (IR) and visual sensing for hunting, and applies this biological inspiration to robotic navigation and target detection. A differential drive robot was designed with dual-sensing capabilities using an Adafruit MLX90640 IR Thermal Camera and Raspberry Pi Camera Module 2 to test the hypothesis that combining IR and vision will outperform single-sensing approaches in navigation and prey detection.
The Challenge
Pit vipers can strike prey even in darkness using pit organs for infrared detection, while also relying on visual cues for navigation and landmark recognition. The challenge was to design a robotic platform that could integrate both sensing modalities and test whether dual-sensing approaches outperform single-sensing methods in target tracking and navigation tasks.
Our Solution
Developed a snake-inspired mechanical platform with dual-sensing capabilities. Implemented thermal image processing using binary masking (>35°C) and centroid calculation via scipy.ndimage.center_of_mass. Created visual image processing using AprilTags for low-power recognition, calculating distance and heading from tag size and pixel location. Integrated both modalities through simple averaging of heading angles with a bang-bang controller for steering control.
Bio-Inspired Gallery

Interactive Model
Exploded assembly view showing component relationships
Key Results
Technologies & Tools
Project Timeline
Research & Design
Literature review on pit viper sensing, mechanical platform design, and sensor selection
- Research paper analysis
- Mechanical design concepts
- Sensor selection and specifications
Platform Development
3D printing and assembly of snake-head inspired robot platform with dual sensing capabilities
- 3D printed mechanical platform
- Sensor integration and mounting
- Power and control system setup
Algorithm Development
Development of thermal and visual image processing algorithms, sensor fusion, and control logic
- Thermal image processing algorithm
- Visual tracking with AprilTags
- Sensor fusion and control algorithms
Testing & Analysis
Comprehensive testing of single and dual sensing modalities with performance analysis
- Performance testing results
- Statistical analysis of TTR and variance
- Research findings and conclusions
Technical Specifications
Key Features
Team
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