Systems Thinking for Sustainable Early-Stage Design of Autonomous Residential Robotic Systems: A Safety-by-Design Framework Evaluated Through an Automated Window-Cleaning Robot

Autonomous robotic systems operating in residential environments must maintain safe, reliable, and adaptive performance under heterogeneous conditions characterized by environmental uncertainty. Achieving this performance is difficult because such systems must simultaneously cope with variable contact states and complex subsystem interactions. Conventional component-oriented engineering approaches often fail to capture how internal faults, external disturbances, and architectural decisions interact to generate system-level instabilities and hazards. This paper proposes a Systems Thinking-based Safety-by-Design framework to support the sustainable early-stage design of autonomous residential robotic systems. The methodology formalizes the relationships among internal faults (F), environmental variability (E), system behaviour (S), architecture (A), instabilities (I), hazards (H), and safety barriers (B) through the dependencies S = f(F,E), I = g(S,A), and H = h(I,B). Environmental variability is treated as an active design driver influencing system behaviour, architectural decisions, and safety requirements. The framework is evaluated as a proof-of-concept, semi-quantitative analytical demonstration, rather than an experimentally validated result, using an autonomous window-cleaning robot: its functional subsystems are mapped to the conceptual model and fault-dominated, environment-dominated, and coupled degradation scenarios are assessed through a semi-quantitative index. The results show that risk emerges from subsystem interactions rather than isolated component failures and that adaptive architectures reduce instability propagation under uncertain operating conditions. The proposed framework supports early engineering decisions that improve robustness, resilience, safety, maintainability, and sustainability.