Domain-specific languages for kinematic chains and their solver algorithms: lessons learned for composable models

摘要

The Unified Robot Description Format (URDF) and, to a lesser extent, the COLLAborative Design Activity (COLLADA) format are two of the most popular domain-specific languages (DSLs) to represent kinematic chains in robotics with support in many tools including Gazebo, MoveIt!, KDL or IKFast. In this paper we analyse both DSLs with respect to their structure and semantics as seen by tools that produce or consume such representations. For the former, we notice a tight coupling of various unrelated domains like kinematics and dynamics with visualisation, control or even specific simulators. For the latter, a key insight is that both DSLs target human developers and leave important design decisions like the choice of joint attachment frames implicit or hidden in the documentation. The lessons learned from this analysis guide us to an improved interchange format by designing composable, loosely coupled models with complete metamodels that unambiguously define the model semantics. We substantiate our findings with concrete examples. Furthermore, we compose solver algorithms on top of the kinematic chain representation. As a consequence of the above analysis and decomposition we can systematically apply structure- and semantics-conserving model-to-code transformations to those algorithms.