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Please refer to the [wiki](https://github.com/ntnu-arl/gbplanner_wiki/wiki) page for detailed instructions to install and run the demo simulations as well as documentation of the planner interface and parameters.
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More results and video explaination of our method can be found on our website: [Link](https://www.autonomousrobotslab.com/exploration-planning.html)
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Hence, to simplify the test process with the planner, we prepare an example workspace [gbplanner_ws](https://github.com/unr-arl/gbplanner_ws), which includes all relevant packages. Please follow the suggested steps in the repo [gbplanner_ws](https://github.com/unr-arl/gbplanner_ws) for further detail.
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## Installation
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These instructions assume that ROS desktop-full of the appropriate ROS distro is installed.
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### How to launch the planner
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- Launch file for simulation:
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```
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roslaunch gbplanner gbplanner_sim.launch
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Install necessary libraries:
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For Ubuntu 18.04 and ROS Melodic:
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```bash
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sudo apt install python-catkin-tools \
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libgoogle-glog-dev \
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ros-melodic-joy \
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ros-melodic-twist-mux \
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ros-melodic-interactive-marker-twist-server
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```
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- To trigger the planner in command line, please use the service call:
- We provide several types of environment for simulation in the package [planner_gazebo_sim](https://github.com/unr-arl/gbplanner_ros/tree/master/planner_gazebo_sim) including room-and-pillar mine (```pittsburgh_mine.world```), long-wall mine (```edgar_mine.world```), and a model reconstructed from a real mine (```virginia_mine.world```)
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### Select the mapping framework
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By default, the planner is compiled with Voxblox. To compile with Octomap, set the flag USE_OCTOMAP to 1:
Also change the config to Octomap in the gbplanner_sim.launch file
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## Running Planner Demo
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### Aerial Robot Demo
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Download the gazebo model from [here](https://drive.google.com/file/d/1Mx_JKNyx2MEwn56LM5KyP8Z3FM-4I6OS/view?usp=sharing) and extract in the `~/.gazebo/models` folder.
In Ubuntu 18.04 with ROS Melodic, the gazebo node might crash when running the ground robot simulation. In this case set the `gpu` parameter to false [here](https://github.com/ntnu-arl/smb_simulator/blob/6ed9d738ffd045d666311a8ba266570f58dca438/smb_description/urdf/sensor_head.urdf.xacro#L20).
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## Results
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Robot's of Team Cerberus running GBPlanner and GBPlanner2
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Autonomous exploration mission in the Prize Round of the DARPA Subterranean Challenge Final Event using four ANYmal C legged robots (Chimera, Cerberus, Camel, Caiman), all running GBPlanner2 independantly.
You could find a short tutorial on the plannning algorithm and the overall architecture on our website: [Link](https://www.autonomousrobotslab.com/subtplanning.html)
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