Merge branch 'master' of https://github.com/mathworks-robotics/Offroad-Navigation-for-Autonomous-Haul-Trucks

Author: roquarrel

README.md

@@ -6,19 +6,19 @@
 
 Hauling material in an open pit mining requires a planning stack capable of both navigating at the global scale and avoiding obstacles during local path following. Navigation Toolbox™ offers planners and controllers that serve well for 2-D indoor planning but they can also be extended for 2.5-D offroad navigation. You can do this by deriving structure from terrain and incorporating heuristics into the planners to account for changes in elevation or slope. The solution proposed by this repository approaches the offroad navigation problem in three steps described in these three MLX files:
 
-1. `CreateRoutePlannerUsingDigitalElevationData.mlx` — Process digital elevation data into a road network for route planning.  
+1. [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=mathworks-robotics/Offroad-Navigation-for-Autonomous-Haul-Trucks&project=AutonomousHaulTruck.prj&file=CreateRoutePlannerUsingDigitalElevationData.mlx) `CreateRoutePlannerUsingDigitalElevationData.mlx` — Process digital elevation data into a road network for route planning.  
 
 ![Figures of the digital elevation data, the road network, and a planned path using the road network](images/digital_elevation_to_road_network.png)  
 
-2. `CreateTerrainAwareGlobalPlanners.mlx` — Create an onramp planner that enables the autonomous haul truck to drive onto the road network while avoiding obstacles. This example also creates a terrain-aware planner for situations where the onramp planner cannot find a path to the road network.  
+2. [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=mathworks-robotics/Offroad-Navigation-for-Autonomous-Haul-Trucks&project=AutonomousHaulTruck.prj&file=`CreateTerrainAwareGlobalPlanners.mlx) `CreateTerrainAwareGlobalPlanners.mlx` — Create an onramp planner that enables the autonomous haul truck to drive onto the road network while avoiding obstacles. This example also creates a terrain-aware planner for situations where the onramp planner cannot find a path to the road network.  
 
 ![Onramp planner and the terrain-aware planner](images/onramp_planner_and_terrain_aware_planner.png)  
 
-3. `CreateLocalPlannerToNavigateGlobalPath.mlx` — Create a planner for following global reference paths while satisfying the kinematic and geometric constraints of the haul truck.  
+3. [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=mathworks-robotics/Offroad-Navigation-for-Autonomous-Haul-Trucks&project=AutonomousHaulTruck.prj&file=CreateLocalPlannerToNavigateGlobalPath.mlx) `CreateLocalPlannerToNavigateGlobalPath.mlx` — Create a planner for following global reference paths while satisfying the kinematic and geometric constraints of the haul truck.  
 
 ![Animation of truck using local planner](images/local_planner.gif)  
 
-Lastly, the repository has the `ModelAndControlAutonomousHaulTruck` MLX file. This file shows how to use Simulink® to integrate the road network and planners into an autonomous navigation stack with logic controlled by Stateflow®.  
+Lastly, the repository has the [![Open in MATLAB Online](https://www.mathworks.com/images/responsive/global/open-in-matlab-online.svg)](https://matlab.mathworks.com/open/github/v1?repo=mathworks-robotics/Offroad-Navigation-for-Autonomous-Haul-Trucks&project=AutonomousHaulTruck.prj&file=ModelAndControlAutonomousHaulTruck.mlx) `ModelAndControlAutonomousHaulTruck` MLX file. This file shows how to use Simulink® to integrate the road network and planners into an autonomous navigation stack with logic controlled by Stateflow®.  
 
 This figure shows the top-level of the autonomous navigation stack.
 ![Autonomous navigation stack Simulink model containing Stateflow logic, the road network, and planners](images/navigation_stack.png)