A course project that earned its way into funded research.
This started as the MCTE5255 Mechatronics Engineering Design project — a four-person
team building a controller for a provided soft robotic rehabilitation glove. I led the
detailed control-system design. After the course, I was recruited as a Research
Assistant in the College of Engineering to take the controller further under a funded
grant on soft robotic actuators for tele-rehabilitation.
The brief was narrow on purpose: don’t redesign the glove, design the controller that
makes it move safely, repeatably, and observably — and prove it on the bench before
anyone talks about a patient.
Problem
Pneumatic soft actuators are nonlinear; open-loop timing can't be trusted.
Air is compressible and the glove’s pressure-to-motion response has delay and hysteresis,
so a fixed inflation time does not give a repeatable finger posture. The controller has to
close the loop on finger bending, sequence inflation and vacuum-assisted extension
without ever fighting itself, and stay inside hard safety limits — all on a compact,
battery-powered, well-documented platform.
A centralized ESP32 coordinates sensing, control, actuation, and telemetry. Low-power
logic is electrically isolated from the higher-current pneumatic loads.
Subsystem
Component
Role
Controller
ESP32 (LOLin D32)
FSM, PID, 12-bit ADC, telemetry
Pressure
12 V diaphragm pump
Inflation / flexion
Vacuum
6 V mini pump (370A)
Active extension
Driver
Cytron MDD10A
20 kHz PWM pump drive
Routing
3/2 solenoid valve + 1-ch relay
Pressure ↔ vacuum switching
Feedback
4.5" flex sensor
Finger-bend estimate (ADC)
The whole control unit comes in under 750 g and within the 50 OMR budget
(~41 OMR of commercial parts).
Final control architecture — one pump, one vacuum source, and a single 3/2 solenoid valve, with flex-sensor feedback closing the loop.
Control Logic
A four-state machine with closed-loop inflation and hysteresis-held extension.
Firmware (C++ / Arduino-ESP32) runs a ~50 Hz loop with 5-sample sensor averaging and a
four-state cycle:
INFLATING — unidirectional PID (Kp 4.0 · Ki 0.1 · Kd 1.5) drives the pressure
pump toward the flexion target (≈ 2800 ADC), with anti-windup and a deadband so it
doesn’t hum near setpoint.
HOLD_FLEX — a low maintenance PWM counters slow leakage to hold the posture.
VACUUMING — pressure off, vacuum on to return toward the open hand (≈ 1850 ADC).
HOLD_VAC — bang-bang hysteresis (±100 ADC) keeps the hand open.
A safety watchdog cuts pump power immediately on overshoot or above an ADC ceiling of
3500, and the state machine structurally prevents pressure and vacuum from ever driving
against each other.
Bench Results
The full rehabilitation cycle ran repeatably under instrumentation.
Tests were run on the physical prototype in the SQU Mechatronics lab and streamed over
serial telemetry (sensor · state · PWM · relay) at 115200 baud.
Test
Target
Result
Flex-sensor calibration
ADC ≈ 1850 / 2800
Met
PID inflation
Smooth rise, no overshoot
Met
Vacuum extension
Returns to open-hand target
Met
Full cycle ×3
Consistent completion
Met
Safety cutoff
PWM → 0 at ADC ≥ 3500
Met
Budget & mass
≤ 50 OMR, < 750 g
Met
Research Extension
What the Research Assistant phase adds.
The funded work extends the validated controller toward:
ROS 2 / micro-ROS integration for motion-pattern adjustment and real-time logging.
EMG intention detection (as a supervisory enable) and IMU posture sensing.
Five-finger independent channels and an ADC-to-joint-angle calibration curve.
Hardware safety — physical emergency stop and pressure-relief — required before any
human-subject testing.
Limitations
Honest boundaries.
This is a research and bench-validation platform — not a clinically approved device,
not patient-ready, and not human-tested. In the course phase, EMG intention detection,
full five-finger control, and ROS 2 were scoped as future work rather than delivered.
The value here is a working, documented controller and the test data that backs it up.
