Overview
The Dash robot platform, developed by Blockbot, is a compact, programmable robot designed to teach coding and robotics concepts. Central to its educational value is a suite of measurement algorithms that turn raw sensor data into meaningful information about the robots environment and motion. This page explains the key algorithms used for distance sensing, orientation estimation, object tracking, and overall system calibration.
Distance Measurement Algorithms
Ultrasonic Sensor (HCSR04)
The ultrasonic module measures distance by emitting a 40kHz sound pulse and timing the echos return. The basic algorithm is:
triggerPin = 5echoPin = 6pulse = 10sstart = pulseIn(echoPin, HIGH)distance_cm = (start / 2) * 0.0343
Key points:
- Speed of sound is approximated as 343m/s at 20C; the factor 0.0343 converts s to centimeters.
- Dividing by two accounts for the roundtrip travel.
- Temperature compensation can be added by adjusting the speedofsound factor.
Infrared Proximity Sensors
IR sensors such as the VL53L0X use timeofflight (ToF) to compute distance. The Dash firmware provides a highlevel readDistance() call that returns millimeters. Internally the algorithm performs:
- Emit a short laser pulse.
- Count the number of clock cycles until photon detection.
- Convert cycles to distance using a calibrated scaling constant.
Because the ToF method works at a few centimeters precision, it is ideal for closerange tasks such as linefollowing or obstacle avoidance.
Orientation & Pose Estimation
Gyroscope & Accelerometer Fusion
Dash incorporates an MPU6050, which provides 3axis gyroscope and accelerometer data. The raw readings are noisy, so a complementary filter or a simplified Kalman filter is used to fuse them into a stable heading angle.
alpha = 0.98 // trust gyroscope 98%dt = currentTime - previousTime// Gyro integrationgyroAngle = previousAngle + gyroZ * dt// Accelerometer angle (only pitch/roll)accAngle = atan2(accY, accZ) * RAD2DEG// Complementary filterheading = alpha * gyroAngle + (1 - alpha) * accAngle
The complementary filter balances fast gyroscope response with the longterm stability of the accelerometer.
Magnetometer (Optional AddOn)
If a magnetometer such as the HMC5883L is attached, a full 3D orientation can be obtained using the Madgwick algorithm. This approach combines gyroscope, accelerometer, and magnetometer data into a quaternion representation, which avoids gimbal lock and provides smooth interpolation for animations.
Object Tracking & Vision
Dash can be equipped with the Dash Camera, a small color sensor that streams frames to a companion app. Simple vision algorithms run on the host device (phone, tablet, or laptop) and feed results back to the robot.
Color Blob Detection
Typical steps for detecting a red ball, for example:
- Convert the RGB frame to HSV color space.
- Threshold the Hue channel around the target hue (e.g., 010 and 350360 for red).
- Apply morphological opening to remove noise.
- Find contours and select the largest area as the target.
- Calculate the contours centroid to obtain pixel coordinates (x, y).
The pixel location is then transformed into a direction command for the robot using the camera's fieldofview (57 horizontally).
Optical Flow for Speed
For tracking moving objects without a specific color, the LucasKanade method can estimate pixel displacement between consecutive frames. The average flow vector magnitude gives an approximate speed, while the direction points towards the objects motion.
Calibration Procedures
Accurate measurements require periodic calibration:
- Ultrasonic sensor: Place a flat board at known distances (10cm, 20cm, 30cm) and record raw echo times. Fit a linear model to correct systematic bias.
- IMU: Perform a 6point static calibration (lying flat, standing on edge, etc.) to estimate bias and scale factors for each axis.
- Magnetometer: Execute a figure8 motion to sample the full magnetic field, then apply an ellipsoid fit to correct hardiron and softiron distortions.
Further Reading & Resources
- Blockbot Dash Learning Portal tutorials, code samples, and sensor datasheets.
- InvenSense MPU6050 Register Map for lowlevel sensor interfacing.
- Madgwick, S.O.H. An efficient orientation filter for inertial and inertial/magnetic sensor arrays. 2010.
- OpenCV documentation CamShift & Blob Detection examples.
