Recompositional Robotics: Cross-Domain, Open-set, and Lifelong Modularity Beyond Morphology
Organizations: Texas Robotics and the Walker Department of Mechanical Engineering, The University of Texas at Austin, Austin, TX 78712, USA
Abstract
Research in modular robotics has produced capable approaches allowing a robot's morphology to change online, with recent efforts also developing approaches to decide which morphology to assume and automatically propagate that decision into the robot's motion planning and control. These approaches are powerful and increase adaptability in the field. However, an alternative objective is not to build robots whose structures can change, but robots whose fundamental capabilities can change, where capability is a joint function across several domains, including kino-dynamics, perception, compute, and high-level coordinating behaviors. A robot designed to be reconfigured across these domains has a greater capacity to alter its capability than one that can be reconfigured in a single domain. We refer to this cross-domain reconfigurability as integration span, and recognize a complementary measure of the resistance to reconfiguration, which we refer to as integration inertia. Current modular robots have reduced integration inertia in the structural domain while it remains high in the other domains that contribute to integration span. We assert that the systems that can provide the most utility through reconfiguration in practice are those maximizing span and minimizing inertia and call this general problem recompositional robotics: adaptation over a heterogeneous set of modules including hardware, software, compute, and behavior that abstracts each component by the interfaces it requires and provides such that they can be reasoned over holistically. We define the problem, ground it in two deployed systems and active research efforts, and pose open questions about the future of recompositional robotics.
Figures & tables
| Thread & Representative Work | Integration Span | Integration Inertia | Open-Set |
| Self-reconfigurable modular robots [ 25 , 3 , 10 ] | HW | Low for morphology only | |
| Task-driven modular platforms [ 17 , 9 , 6 ] | HW | Low for morphology and kino-dynamic model only | |
| Plug-and-produce [ 20 , 16 , 7 ] | HW | Low for registered and preconfigured devices only | |
| Self-adaptive software [ 1 , 15 , 24 ] | SW | Low within variant space | |
| Task and behavior planning [ 5 , 12 , 13 ] | Behavior | Low for top-level plan generation only | |
| Monotone co-design [ 4 , 26 , 14 ] | HW, SW, compute | High, requires offline re-modeling |