1. Introduction
In warehouses, robots are used to move and sort packages. Sometimes, robots fail to complete tasks due to obstacles, wrong path selection, or low battery.
This case study shows how a machine learning system can help predict whether a robot will successfully complete a task and improve its performance.
2. Problem Statement
We want to build a system that can:
Predict whether a robot task will be:
- Successful
- Failed
Based on:
- Distance from obstacles
- Battery level
- Load weight
- Path length
Output:
- Task Success (Yes / No)
3. Data Collection
- Data is collected from robot operations
- Each record contains:
- Input values (battery, load, distance, etc.)
- Output label (Success / Failure)
Since output is already given → this is Labeled Data
So, this is a Supervised Learning problem
4. Data Preprocessing
✔ Handling Missing Values
- Fill missing values using average or most common value
✔ Encoding Labels
- Success = 1
- Failure = 0
✔ Feature Scaling (optional)
- Normalize values like battery and distance if needed
5. Feature Selection
Important inputs:
- Battery level
- Distance from obstacle
- Load weight
- Path length
6. Train-Test Split
- Divide data into:
- Training data (to train model)
- Testing data (to check accuracy)
7. Model Selection
Since output is Yes/No → Classification problem
We use:
✔ Decision Tree Classifier
Reason:
- Easy to understand
- Creates simple rules
- Works well for small datasets
8. Model Training
- The model learns patterns from training data
Example learned rules:
- If battery is low → Failure
- If obstacle distance is small → Failure
- If battery is high and path is clear → Success
These rules are learned automatically
9. Model Testing
- Test the model using new data
- Model predicts:
- Success or Failure
10. Model Evaluation
Check performance using:
- Accuracy
- Confusion Matrix
Important:
- Correctly predicting failures is very important
11. Model Deployment
- Model is connected to robot system
- It predicts task outcome in real time
If failure predicted:
- Robot can change path
- Robot can stop or recharge battery