Context-aware system synthesis, task assignment, and routing

The design and organization of complex robotic systems traditionally requires laborious trial-and-error processes to ensure both hardware software components are correctly connected with the resources necessary for computation. This paper presents a novel generalization quadratic assignment routing problem, introducing formalisms selecting interconnections synthesize complete system capable providing some user-defined functionality. By mission context, functional requirements, modularity directly into we derive solution where automatically selected placed an optimal software, all while respecting restrictions on component viability required ability generate from individual reduces manual effort by allowing guided exploration space. Additionally, our formulation increases resiliency quantifying resource margins enabling adaptation structure in response changing environments, or failure. proposed is cast as integer linear program which provably $${\mathcal {N}}{\mathcal {P}}$$ -hard. Two case studies analyzed highlight expressiveness complexity problems that addressable this approach: first explores iterative development ground-based search-and-rescue robot varying contexts, second compares automated humanoid against was finalist DARPA Robotics Challenge. Numerical simulations quantify real-world performance demonstrate tractable time scale encountered many modern systems.