Warehouse Robot Simulation

Demonstrates how to execute an obstacle-free path for a mobile robot between three locations on a given map. The robot is expected to visit the three locations in a warehouse: a charging station, loading station, and unloading location. The sequence in which these locations are visited is dictated by a scheduler. The scheduler gives each robot a goal pose to navigate to. The robot plans a path and uses a Pure Pursuit controller to follow the waypoints based on the current pose of the robot. The Differential Drive Kinematic Model block models the simplified kinematics, which takes the linear and angular velocities from the Pure Pursuit Controller. This example builds on top of the Plan Path for a Differential Robot in Simulink example.

Simulate a warehouse robot in Gazebo. Gazebo enabled you to simulate a mobile robot that uses a range sensor, while executing certain tasks in a simulated environment. This example details how to use a simulator to apply the Execute Tasks for A Warehouse Robot example, where a robot delivers packages in a warehouse scenario. The robot makes use of the simulated range sensor in Gazebo to detect possible collisions with a dynamic environment and avoid them.

Control and simulate multiple robots working in a warehouse facility or distribution center.

Control multiple robots working in a distribution center, as well as how to easily configure a distribution system. The robots navigate the facility and complete multiple tasks while leveraging algorithms from game theory to optimize task allocation between robots and resolving conflicts using a grid-based traffic manager. This example builds on the information covered in the Control and Simulate Multiple Robots example, which navigates multiple robots around a similar facility, but this example uses custom algorithms.

Create a scenario to simulate two mobile robots performing obstacle avoidance in a warehouse. This example demonstrates how to create a warehouse scenario, add mobile robots using the rigid body tree representation, model the kinematics of the robots, and simulate the behavior of the control algorithms using the resultant scenario.