- Making collision maps from self-filtered laser data
This tutorial introduces the processing pipeline that takes scans from the tilting laser on the PR2, self-filters the robot from the data, and constructs a collision map that can then be used for checking potential collisions.
- Checking collisions for a joint trajectory
This tutorial will show you how to check whether an input joint trajectory is in collision, violates joint limits or satisfies constraints.
- Checking collisions for a given robot state
This tutorial will show you how to use the environment server with laser collision map data to check whether a given robot state is collision free, within the joint limits and satisfies joint or cartesian constraints.
- Adding known objects to the motion planning environment
This tutorial will introduce the topic of adding known objects to the collision environment. Known objects are shapes that have been recognized by a semantic perception pipeline or are known to exist at particular positions by a system designer.
- Attaching objects to the robot's body
This tutorial describes methods by which known objects can be attached to a robot's body. Attaching an object to the body means that the object will move when the robot moves; this functionality allows motion planners and the trajectory monitor to deal with situations where the robot has grasped something and avoiding collisions between the grasped object and the environment becomes important.
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