How to represent aspects of the paper "Learning agile and dynamic motor skills for legged robots" in Gazebo?
I am currently reading the paper Learning agile and dynamic motor skills for legged robots. The paper claims that robotic behavior learned in simulation is difficult to transfer to a real-world situation as a realistic simulation is difficult. The authors, therefore, enrich a typical simulation substantially. To quote:
Our key insight on the simulation side is that efficiency and realism can be achieved by combining classical models representing well-known articulated system and contact dynamics with learning methods that can handle complex actuation. The rigid links of ANYmal, connected through high-quality ball bearings, closely resemble an idealized multibody system that can be modeled with well-known physical principles (40). However, this analytical model does not include the set of mechanisms that map the actuator commands to the generalized forces acting on the rigid-body system: the actuator dynamics, the delays in control signals introduced by multiple hardware and software layers, the low-level controller dynamics, and compliance/damping at the joints. Because these mechanisms are nearly impossible to model accurately, we learned the corresponding mapping in an end-to-end manner
I am asking myself how to represent these things in a Gazebo simulation. In particular:
- Are the rigid links represented by the collision, visual, and inertial properties in a URDF file?
- How are the torque commands represented in Gazebo? Do they correspond to the tags inside a joint's description in a robot's URDF file?
- Is it possible to refer to an external program in Gazebo to calculate the torque forces during the simulation based on some publications from ROS instead of specifying these things inside a URDF file?
Asked by fabian on 2020-07-31 04:57:56 UTC
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