Project Overview
This checkpoint project focused on progressively increasing the autonomy of the RB-1 warehouse robot to navigate and handle objects in a simulated warehouse environment. The project evolved through three distinct phases, each building upon the previous one to achieve full autonomous operation.
Starting from basic hardcoded navigation, the robot gradually developed advanced capabilities including simultaneous localization and mapping (SLAM), obstacle detection, and fully autonomous path planning - demonstrating the complete progression from manual control to intelligent autonomy.
My Role
I developed the navigation and mapping software for all three phases of the project, implementing and tuning algorithms for each level of autonomy. This included:
- Programming hardcoded navigation paths and object manipulation routines
- Implementing SLAM algorithms for real-time mapping and localization
- Configuring path planning algorithms for autonomous navigation
- Tuning sensor processing and obstacle detection parameters
- Testing and validating each phase of automation in simulation
Three-Phase Development Process
Phase 1: Hardcoded Navigation
Foundation - Predefined Path Following
In the initial phase, the robot followed a predefined, hardcoded path to complete its warehouse tasks. The robot was programmed with specific coordinates and commands to:
- • Navigate to a specific shelf location using predetermined waypoints
- • Lift and attach the shelf to the robot base
- • Transport the shelf along a fixed route to the drop-off location
- • Release the shelf at the designated position
This phase established the basic motion control and object manipulation capabilities needed for warehouse operations.
Phase 2: SLAM-Based Mapping
Environmental Awareness - Mapping & Localization
The second phase introduced Simultaneous Localization and Mapping (SLAM), enabling the robot to understand its environment dynamically:
- • Real-time mapping of the warehouse environment using laser scanner data
- • Continuous localization to track the robot's position within the generated map
- • Obstacle detection capabilities using sensor fusion
- • Basic path planning to navigate around detected obstacles
- • Map storage and reusability for future navigation tasks
This phase introduced environmental perception, allowing the robot to adapt to changes in the warehouse layout.
Phase 3: Full Autonomy
Complete Independence - Autonomous Operation
The final phase achieved complete autonomous operation, where the robot could independently plan and execute warehouse tasks:
- • Autonomous navigation using the previously generated map
- • Dynamic path planning to reach any specified goal location
- • Real-time obstacle avoidance and re-planning capabilities
- • Autonomous shelf identification, pickup, and delivery
- • Complete task execution from start to finish without human intervention
This phase demonstrated true robotic autonomy, with the robot making intelligent decisions to accomplish warehouse logistics tasks.
Technologies Used
Simulation Screenshots
Simulation Environment - RB-1 Warehouse Robot
Screenshots showing robot navigation, SLAM mapping, and autonomous shelf handling
Impact & Learning Outcomes
This project demonstrated a comprehensive understanding of robotic autonomy progression. By developing the robot through three distinct phases, I gained hands-on experience with fundamental robotics concepts:
- Motion control and trajectory planning
- Simultaneous localization and mapping (SLAM) implementation
- Autonomous path planning and obstacle avoidance
- Sensor integration and data processing
- Robotic manipulation for warehouse logistics