# Behavior-Based Control Architecture for Legged-and-Climber Robots
## 2 Related Work  
Control architectures are found within autonomous machines, especially in spacecraft. The increasing development of these vehicles has generated generic architectures that may be used in any system. Within the state of the art, we can find Contextual Management of Tasks and Instrumentation (CMTI), which is a mixed architecture between deliberative and reactive architectures [9], originally conceived for an autonomous underwater vehicle (AUV). It is organized into three layers: global supervisory control, local supervisory control and low-level control. CMTI is a well-defined and robust architecture but laborious to implement in short projects. Based on CMTI, Contextual Task Management Architecture (COTAMA) is a control software architecture layered into two levels [10]: decisional level and executive level. The decisional level is in charge of the mission monitoring and decision making according to robot context. The executive level applies these decisions while managing all real-time aspects such as instrumentation conflicts or tasks deadlines. It contemplates the identification of faults to correct them [11]. COTAMA improves the robustness of CMTI while it enlarges the possible applications; however, like CMTI, it is very laborious to implement. Remote Agent architecture (RA) is an autonomous control system capable of closed-loop commanding of spacecraft and other complex systems [12]. It integrates three layers of functionality: a constraint-based planner/scheduler, a reactive executive, and a model identification and recovery system. RA is very useful for spacecraft; however, its usefulness is limited to tasks previously defined in detail. Intelligent Distributed Execution Architecture (IDEA) was created to duplicate RA architecture within a unified agent framework where all the layers have the same structure [12]. IDEA improves the coordination of RA; however, the drawbacks are similar. Laboratory for Analysis and Architecture of Systems (LAAS) architecture is presented in [13] as an architecture for reflexive autonomous vehicle control. It decomposes the robot software into three main levels, having different temporal constraints and manipulating different data representations. LAAS is thought to improve robustness; however, it is poorly-defined and very open to the developer. Coupled Layer Architecture for Robotic Autonomy (CLARAty) is designed for improving the modularity of system software while more tightly coupling the interaction of autonomy controls [14]. According to the CLARAty developers, typical robot and autonomy architectures comprise three levels: functional, executive and planner. To correct the shortfalls in the three-level architecture, they propose a two-tiered architecture, in which the executive and planner layers are combined. As well as LAAS, CLARaty is very open to the user because it only describes the two main levels. Cooperative Intelligent Real-Time Control Architecture (CIRCA) was designed in [15] to guarantee the control-level goals, but not necessarily the task-level goals. They divide the architecture into three main parts: the real-time subsystem (RTS) that is responsible for implementing the responses, the AI subsystem (AIS) that decomposes task-level goals into plans consisting of several phases, and the scheduler. CIRCA has the limitations that it only works for well-known and defined problems. Open Robot Controller Computer Aided Design (ORCCAD) architecture is an open architecture where qualified users have access to every control level: the application layer is accessed to by the end-user of the system, the control layer is programmed by an automatic control expert, and the lowest one, the system layer, is overseen by a system engineer [16]. ORCCAD has the problem that the system's complexity may increase exponentially with new fault tolerance techniques, while the organization structure may become untenable. The described architectures are generic for any system; however, their application in legged-and-climber robots may be laborious and complex.