| Name | kompass-core JSON |
| Version |
0.3.0
JSON |
| download |
| home_page | None |
| Summary | Navigation Algorithms for Kompass |
| upload_time | 2024-11-25 19:38:59 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | <3.13,>=3.8.4 |
| license | MIT License Copyright (c) 2024 Automatika Robotics Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
robotics
robots
navigation
control
planning
mapping
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Kompass Core
Kompass Core is a motion planning and control package for robot navigation. The package contains C++ implementation for core algorithms along with Python wrappers. It also implements third party integrations with [OMPL](https://ompl.kavrakilab.org/) and [FCL](https://github.com/flexible-collision-library/fcl). This package is developed to be used with [Kompass](https://github.com/automatika-robotics/kompass) package for creating navigation stacks in [ROS2](https://docs.ros.org/en/rolling/index.html). For detailed usage documentation, check Kompass [docs](https://automatika-robotics.github.io/kompass/).
## Installation
### Install Dependencies
- `sudo apt-get install libompl-dev libfcl-dev libpcl-dev`
### Install with pip
Wheels are available on Pypi for linux x86_64 and aarch64 architectures.
- `pip install kompass-core`
### Install from Source
- `git clone https://github.com/automatika-robotics/kompass-core`
- `cd kompass-core`
- `pip install .`
Installation with pip will install three Python package:
- `kompass_core`: The main Python API containing all the wrappers and utilities for motion planning and control for navigation in 2D spaces.
- `kompass_cpp`: Pybind11 python bindings for Kompass core C++ library containing the algorithms implementation for path tracking and motion control.
- `ompl`: Bespoke Pybind11 python bindings for the Open Motion Planning Library (OMPL).
## Testing
### Run Planning Test
- `cd tests`
- `python3 test_ompl.py`
To test path planning using OMPL bindings a reference planning problem is provided using Turtlebot3 Waffle map and fixed start and end position. The test will simulate the planning problem for all geometric planners for the number of desired repetitions to get average values.
### Run Controllers Test
- `cd tests`
- `python3 test_controllers.py`
The test will simulate path tracking using a reference global path. The results plot for each available controller will be generated in tests/resources/control
## Usage Example
```python
from kompass_core.control import DVZ
from kompass_core.models import (
AngularCtrlLimits,
LinearCtrlLimits,
Robot,
RobotCtrlLimits,
RobotGeometry,
RobotType,
)
from nav_msgs.msg import Path
# Setup the robot
my_robot = Robot(
robot_type=RobotType.ACKERMANN,
geometry_type=RobotGeometry.Type.CYLINDER,
geometry_params=np.array([0.1, 0.4]),
)
# Set the robot control limits
robot_ctr_limits = RobotCtrlLimits(
vx_limits=LinearCtrlLimits(max_vel=1.0, max_acc=5.0, max_decel=10.0),
omega_limits=AngularCtrlLimits(
max_vel=2.0, max_acc=3.0, max_decel=3.0, max_steer=np.pi
),
)
# Set the control time step (s)
control_time_step = 0.1 # seconds
# Initialize the controller
dvz = DVZ(
robot=my_robot,
ctrl_limits=robot_ctr_limits,
control_time_step=control_time_step,
)
# Set the reference path
global_path : Path = Path()
# Set the reference path for the motion control
dvz.set_path(global_path)
# Get the sensor data
laser_scan = LaserScanData()
# At each control step run
dvz.loop_step(current_state=robot.state, laser_scan=laser_scan)
```
## Copyright
The code in this distribution is Copyright (c) 2024 Automatika Robotics unless explicitly indicated otherwise.
Kompass Core is made available under the MIT license. Details can be found in the [LICENSE](LICENSE) file.
## Contributions
Kompass Core has been developed in collaboration between [Automatika Robotics](https://automatikarobotics.com/) and [Inria](https://inria.fr/). Contributions from the community are most welcome.
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"description": "# Kompass Core\n\nKompass Core is a motion planning and control package for robot navigation. The package contains C++ implementation for core algorithms along with Python wrappers. It also implements third party integrations with [OMPL](https://ompl.kavrakilab.org/) and [FCL](https://github.com/flexible-collision-library/fcl). This package is developed to be used with [Kompass](https://github.com/automatika-robotics/kompass) package for creating navigation stacks in [ROS2](https://docs.ros.org/en/rolling/index.html). For detailed usage documentation, check Kompass [docs](https://automatika-robotics.github.io/kompass/).\n\n## Installation\n\n### Install Dependencies\n\n- `sudo apt-get install libompl-dev libfcl-dev libpcl-dev`\n\n### Install with pip\n\nWheels are available on Pypi for linux x86_64 and aarch64 architectures.\n\n- `pip install kompass-core`\n\n### Install from Source\n\n- `git clone https://github.com/automatika-robotics/kompass-core`\n- `cd kompass-core`\n- `pip install .`\n\nInstallation with pip will install three Python package:\n\n- `kompass_core`: The main Python API containing all the wrappers and utilities for motion planning and control for navigation in 2D spaces.\n- `kompass_cpp`: Pybind11 python bindings for Kompass core C++ library containing the algorithms implementation for path tracking and motion control.\n- `ompl`: Bespoke Pybind11 python bindings for the Open Motion Planning Library (OMPL).\n\n## Testing\n\n### Run Planning Test\n\n- `cd tests`\n- `python3 test_ompl.py`\n\nTo test path planning using OMPL bindings a reference planning problem is provided using Turtlebot3 Waffle map and fixed start and end position. The test will simulate the planning problem for all geometric planners for the number of desired repetitions to get average values.\n\n### Run Controllers Test\n\n- `cd tests`\n- `python3 test_controllers.py`\n\nThe test will simulate path tracking using a reference global path. The results plot for each available controller will be generated in tests/resources/control\n\n## Usage Example\n\n```python\nfrom kompass_core.control import DVZ\n\nfrom kompass_core.models import (\n AngularCtrlLimits,\n LinearCtrlLimits,\n Robot,\n RobotCtrlLimits,\n RobotGeometry,\n RobotType,\n)\nfrom nav_msgs.msg import Path\n\n# Setup the robot\nmy_robot = Robot(\n robot_type=RobotType.ACKERMANN,\n geometry_type=RobotGeometry.Type.CYLINDER,\n geometry_params=np.array([0.1, 0.4]),\n )\n\n# Set the robot control limits\nrobot_ctr_limits = RobotCtrlLimits(\n vx_limits=LinearCtrlLimits(max_vel=1.0, max_acc=5.0, max_decel=10.0),\n omega_limits=AngularCtrlLimits(\n max_vel=2.0, max_acc=3.0, max_decel=3.0, max_steer=np.pi\n ),\n)\n\n# Set the control time step (s)\ncontrol_time_step = 0.1 # seconds\n\n# Initialize the controller\ndvz = DVZ(\n robot=my_robot,\n ctrl_limits=robot_ctr_limits,\n control_time_step=control_time_step,\n )\n\n# Set the reference path\nglobal_path : Path = Path()\n\n# Set the reference path for the motion control\ndvz.set_path(global_path)\n\n# Get the sensor data\nlaser_scan = LaserScanData()\n\n# At each control step run\ndvz.loop_step(current_state=robot.state, laser_scan=laser_scan)\n```\n\n## Copyright\n\nThe code in this distribution is Copyright (c) 2024 Automatika Robotics unless explicitly indicated otherwise.\n\nKompass Core is made available under the MIT license. Details can be found in the [LICENSE](LICENSE) file.\n\n## Contributions\n\nKompass Core has been developed in collaboration between [Automatika Robotics](https://automatikarobotics.com/) and [Inria](https://inria.fr/). Contributions from the community are most welcome.\n",
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