Distributed vs. Hybrid Control Architecture Using STPA and AHP - Application to an Autonomous Mobile Multi-robot System

Abstract

Systems composed of a fleet of autonomous mobile robots are among the most complex control systems. This control complexity is at a high level especially when those robots navigate in hazardous and dynamic environments such as chemical analysis laboratories. These systems include different dangerous and harmful products (toxic, flammable, explosive...) with different quantity. In order to perform its mission on a regular basis, this multi-robot system can be controlled according to multiple architectures. We propose, firstly, to apply the System Theoretic Process Analysis (STPA) on two selected control architectures, namely distributed and hybrid architectures in order to obtain a set of loss scenarios for each kind of architecture. For further assessment, the Analytic Hierarchy Process (AHP) is used to choose the best architecture. The proposed approach provides a risk analysis and a more practical comparison between the two control architectures of a mobile multi-robot system and facilitates decision-making, even in complex situations.

STPA for Learning-Enabled Systems: A Survey and A New Practice

“…Autonomous ships and drones are also studied in [58], [49], [27], [61], [5] and [16], respectively. Collaborative robots [11], [3], [14] and Autonomous Mobile Multi-robots [9], [10], [14], [12] are also active areas of applying STPA. Moreover, STPA-priv was initially implemented for smart televisions [53] before being extended to E-health [39], recognising that privacy is a vital concern for humans.…”

“…It is also feasible to integrate STPA with hierarchical modelling approaches for intricate systems [50], [31]. STPA may jointly analyse with Analytic Hierarchy Process (AHP) [10] and Stochastic Petri Nets (SPN) [12] respectively and recommend new safety requirements. The advancements have been made in the integration of STPA with domain-specific safety frameworks for autonomous vehicles and ships, e.g.…”

“…• R2: Maintain a balance between exploration and exploitation in reinforcement learning, it can be employed state-of-the-art methods like the ε-greedy approach 9 . • R3: Incorporate an experience replay 10 .…”

“…9 The ε-greedy approach is a strategy that enables the agent to explore different actions while also exploiting the currently known optimal actions. 10 Replaying past experiences during training helps the model learn from diverse sets of data, enhancing efficiency and stability. 11 Reward shaping is a technique that involves adding additional reward signals to guide the RL agent during training.…”

Application of Systems Theoretic Process Analysis and Failure Modes and Effects Analysis to Process Reliability and Occupational Safety and Health in Construction Projects

“…Since its proposal, the STPA has been implemented in different areas, ranging from technical reliability, maritime systems, healthcare, software projects, cyber security, process industry, nuclear power plants, to autonomous systems [9][10][11][12][13][14][15][16][17][18][19][20][21][22][23][24][25][26]. Unsurprisingly, various papers have been published concerning the application of the STPA in autonomous systems, for these systems work with little or no human intervention, and rely on a hierarchy of controllers to function continuously and reliably.…”