2021 Autonomous Systems & Robotics

Autonomous RC Rover

A planetary rover platform designed to complete three missions around the Olin oval: navigating the "wasteland", docking at a station, and payload dropping. The rover uses multiple sensing methods including IR sensors, sonar, and computer vision for navigation.

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Team Size

6

Multidisciplinary engineering team

Sensing

8

Input devices (5 IR, 2 Sonar, 1 PiCam)

Missions

3

Complex navigation challenges completed

The Challenge

Building an autonomous rover capable of navigating complex environments presented several key challenges:

  • Developing reliable sensor integration for different environmental conditions
  • Creating a robust control system for navigation in unstructured environments
  • Implementing computer vision algorithms for path finding and April Tag detection
  • Designing a mechanical system that could carry payloads and operate reliably
  • Building a power distribution system that supported both logic and motor circuits
Rover Mission Path

The Solution

We developed an integrated autonomous system featuring:

  • Sensor suite with five IR sensors at different angles for wall detection
  • Pan/tilt turret with PiCam and two sonar sensors for environmental sensing
  • Computer vision system for path finding and April Tag recognition
  • Custom payload claw mechanism for object manipulation
  • Dual-circuit power system with separated logic and motor supplies
Rover Mission 2

Rover in action

The mechanical system consisted of several key components designed for modularity and functionality:

  • Sensor suite with five IR sensors mounted at different angles (30° apart) for detecting walls and obstacles
  • Pan/tilt turret with PiCam and two sonar sensors for improved environmental awareness
  • Main body constructed from Sentra board providing anchor points and structural support
  • Payload claw mechanism with interlocking gear design for reliable object manipulation
  • Enclosed battery housing to protect components from environmental conditions

Technical Implementation

The rover featured two main circuits running in parallel:

Motors Circuit: Powered by a 7.2V battery connected to an E-Stop button for safety. Power was distributed between an Electronic Speed Control board and a power distribution board (PDB) connected to a PiHAT for communication with the Raspberry Pi. This circuit controlled four servos (one for steering, one for the claw, and two for the pan/tilt turret) and the main drive motor.

Logic Circuit: Connected eight input devices (5 IR sensors, 2 sonar sensors, and 1 PiCam) to two Qwiic boards that provided power and communicated with the Raspberry Pi through a PiHAT connector. The PiCam connected directly to the Pi through a built-in ribbon connector.

Rover Circuit Diagram

Rover Power and Control System

Software Architecture

The control software was implemented in Python and structured around three main missions:

Mission 1 (Wasteland): Combined hardcoded initial turns with IR sensor-based wall approach and sonar-based wall following. The system would measure distance from the wall through sonar sensors and determine whether to turn right, left, or go straight to maintain a constant distance.

Mission 2 (Docking): Used April Tag detection for intersection identification and navigation decisions. After turning at an intersection, the rover implemented color masking and path finding through image processing, analyzing each frame to identify the path and determine direction.

Mission 3 (Payload Drop): Combined elements from previous missions with specific payload dropping behaviors. Once the rover detected the appropriate April Tag (ID 4, 5, or 6), it would approach the payload station, and when close enough, send a signal to the servo controlling the claw to open and release the payload.

Rover Claw

Rover Claw Mechanism

Mission Performance

Mission 1: Wasteland

  • Successfully navigated out of the starting dock
  • Completed left turn and advanced toward the MAC wall
  • Maintained wall-following behavior with IR and sonar sensors
  • Autonomously navigated most of the course with only one manual intervention
  • Reached the end of the building and stopped appropriately

Mission 2: Docking

  • Successfully exited starting dock and navigated toward the curb
  • Made appropriate turn at the intersection after detecting April Tag
  • Used image masking for path finding along the central route
  • Recognized docking station April Tag and initiated docking sequence
  • Successfully stopped approximately 2 inches from the wall

Mission 3: Payload Drop

  • Effectively followed the same path as in Mission 2
  • Correctly identified the April Tag for the payload drop location
  • Successfully approached the payload box at an appropriate speed
  • Stopped at the correct distance from the target
  • Successfully opened the claw mechanism to drop the payload

Challenges Overcome

  • Steering servo failure requiring last-minute recalibration
  • Connectivity issues when transitioning between WiFi networks
  • Physical obstacles like granite blocks causing temporary path deviations
  • Integration challenges between mechanical, electrical, and software systems
  • Limited timeline and budget constraints
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