Decision Package

1. Overview

The decision_package implements a ROS 2 decision-making node that processes obstacle data and determines robot behavior.

It acts as an intermediate intelligence layer between perception and actuation.

Purpose

Interpret obstacle detection results
Classify risk levels
Generate appropriate motion commands
Forward commands to the motor control system

2. System Architecture

/obstacle_clusters
        ↓
   decision_node
        ↓
/motor_command
        ↓
   motor_node
        ↓
    Arduino
        ↓
   Motor + Servos

3. Package Description

Package Name

decision_package

Node Name

decision_node

Language

Python (rclpy)

4. ROS Interfaces

4.1 Subscribed Topic

Topic	Type	Description
`/obstacle_clusters`	`std_msgs/msg/String`	Obstacle classification data

4.2 Published Topic

Topic	Type	Description
`/motor_command`	`std_msgs/msg/String`	Motor control commands

5. Input Data Format

The node expects obstacle classification as a string containing keywords.

Supported Keywords

Keyword	Meaning
`SAFE`	No obstacle
`MODERATE`	Obstacle nearby
`CRITICAL`	Immediate danger

Example Inputs

"SAFE"
"MODERATE obstacle detected"
"CRITICAL"

6. Decision Logic

The node evaluates incoming data and maps it to motor commands.

Logic

if "CRITICAL" in data:
    command = "STOP"
elif "MODERATE" in data:
    command = "F80"
else:
    command = "F150"

Behavior Mapping

Condition	Output Command	Description
CRITICAL	`STOP`	Immediate stop
MODERATE	`F80`	Slow forward
SAFE	`F150`	Normal forward

7. Output Command Protocol

Commands are compatible with the Arduino motor protocol.

Motor Commands

F<speed>   → Forward
B<speed>   → Backward
STOP       → Stop

Examples

F150
F80
STOP

8. Execution Flow

Receive obstacle data
Convert to uppercase
Match keyword
Generate motor command
Publish to /motor_command
Motor node forwards to Arduino

9. Integration with Motor Package

This package does NOT directly communicate with hardware.

Instead:

It publishes commands
arduino_motor package handles serial communication

Correct Integration

decision_node → /motor_command → motor_node → Arduino

10. Installation & Setup

10.1 Add to Workspace

cd ~/ros2_ws/src
cp -r decision_package .

10.2 Install Dependencies

cd ~/ros2_ws
rosdep install --from-paths src --ignore-src -r -y

10.3 Build

colcon build

10.4 Source Workspace

source install/setup.bash

10.5 Run Node

ros2 run decision_package decision_node

11. Testing

Publish Test Data

ros2 topic pub /obstacle_clusters std_msgs/msg/String "{data: 'SAFE'}"
ros2 topic pub /obstacle_clusters std_msgs/msg/String "{data: 'MODERATE'}"
ros2 topic pub /obstacle_clusters std_msgs/msg/String "{data: 'CRITICAL'}"

Monitor Output

ros2 topic echo /motor_command

12. Design Considerations

Advantages

Clear separation of perception and control
Modular ROS architecture
Easy to extend decision logic
Compatible with existing Arduino protocol

Limitations

Uses string-based messages (not structured)
Keyword matching is fragile
No probabilistic decision-making
No feedback loop

13. Future Improvements

Replace strings with custom ROS messages
Add velocity-based control (/cmd_vel)
Introduce state machine or behavior tree
Integrate sensor fusion
Add feedback from motor system

14. Summary

The decision_package provides a lightweight decision-making layer that:

Interprets obstacle data
Converts it into motor commands
Interfaces cleanly with the motor control package

It forms a critical part of a ROS-based autonomous control pipeline, enabling reactive behavior based on environmental perception.

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