Open jgvictores opened 6 years ago
cc: @PeterBowman @rsantos88
If results are in Cartesian space, keep close integration with kinematics-dynamics, which treats Cartesian to joint space conversions. Therefore, new issues will potentially arise at kinematics-dynamics too.
Regarding trajectories in Cartesian space, new related issues for keeping close integration: https://github.com/roboticslab-uc3m/kinematics-dynamics/issues/134 and https://github.com/roboticslab-uc3m/kinematics-dynamics/issues/135
Regarding trajectories in joint space, just a reminder that we have some tools in the, well, tools repository. Namely, as commented here:
Specifically, you'll want the PlaybackThread. You can find an example of use at examplePlaybackThread and its corresponding test.
See also: https://github.com/personalrobotics/aikido.
AIKIDO is a C++ library, complete with Python bindings, for solving robotic motion planning and decision making problems. This library is tightly integrated with DART for kinematic/dynamics calculations and OMPL for motion planning. AIKIDO optionally integrates with ROS, through the suite of aikido_ros packages, for execution on real robots.
Not exactly path-planning, but kinda related: https://github.com/robotology/navigation.
I think the demo developed by @elisabeth-ms has some bits of path planning. It's an DL-based object detection app for grabbing stuff with one of TEO's arms.
I think the demo developed by @elisabeth-ms has some bits of path planning. It's an DL-based object detection app for grabbing stuff with one of TEO's arms.
Cool, nice catch! I'm totally seeing some OMPL at https://github.com/elisabeth-ms/teo-sharon/blob/cfc3a62270e130d0f3a8a8418c18b1a901508bea/programs/TrajectoryGeneration/TrajectoryGeneration.hpp#L17-L24 in addition to the KDL and FCL code. Thanks!
See also this grasping demo featuring the iCub: https://github.com/robotology/community/discussions/573.
Moar grasping straight from the ongoing Nvidia GTC AI conference (thanks @imontesino):
Thoughts about path-planning within roboticslab-uc3m, and considerations on creating a path-planning repository within the organization.
Considerations to be taken into account before blindly doing this:
As seen, the above candidates already have their place. Therefore, my recommendations are the following: