A Unified Framework for Perception in Autonomous Systems

A Unified Framework for Perception in Autonomous Systems Ignacio L´opez (ilopez@etsii.upm.es) Ricardo Sanz (ricardo.sanz@upm.es) Julita Bermejo (jbermejo@etsii.upm.es) Autonomous Systems Laboratory (ASLab), Universidad Polit´ecnica de Madrid (UPM). Jos´e Guti´errez Abascal, 2. Madrid 28006 Spain Abstract This paper presents the top level goals and perception con- cepts of the ASys Framework. This is an unified framework for cognitive, autonomous systems to be used both in the anal- ysis of natural phenomena and in the synthesis of artificial au- tonomous systems. Perception in ASys is conceived within an holonic, systemic concept, not as an isolated phenomenon. This general perspective allows: (1) Integrating the main ap- proaches to perception developed so far (a brief comparative analysis is offered). (2) A coherent framework for system anal- ysis and design. Keywords: Perception; cognition; embodied cognition; au- tonomous systems; cognitive systems; engineering. Introduction: Motivation and Context In spite of the advances in artificial systems, many tasks are still out of their capacities. Advanced context recognition, decision-making, high degrees of autonomous operation (in uncontrolled environments) and efficient social interaction are examples of them. They represent major drives for the research in advanced cognitive systems and affective com- puting (Ca˜namero & et al., 2004; Picard, 1998). Bioinspired architectures, algorithms and processes were thought to al- low designing more efficient, intelligent and dependable arti- ficial systems. However, it is not the easy path that we once thought. On one side, the substrates of natural and artificial systems present important differences of structural nature. Their prop- erties are so diverse that overcoming the disparity of their structural constraints is extremely difficult. As a result, the type of processes that can be efficiently implemented in artifi- cial substrates is radically different from natural ones. On the other side, biological systems are not known well enough yet. Isolated, low-level phenomena have been traced and mod- elled on one end, and psychological explanations for high- level phenomena have been built on the other. But there does not exist a common, unique, integrated theory explaining all. In our view, the solution to the problem does not rely on just biomimetic approaches or on classical engineering pat- terns of design. An effort in building a general theory which integrates concepts, relations and principles must be made. A sufficient level of generality would allow analyzing and conceptualizing the natural and the artificial upon a common background. This is what we call the ASys approach. In this way bioinspiration would be possible at a conceptual level, in spite of implementational differences at lower ones. Obviously the abstraction back-step from reality that this approach imposes will render a theory that may be missing some details of relevance in current analyses of autonomy and perception. However we believe that these details will be re- gained, placed in their proper place and better grounded on further elaborations of the theory for specific domains. The approach to perception exposed here forms part of ASys and must be necessarily understood within the goals, resources, operation and constraints of a concrete observer system —a perceptor. An observer system may carry out mul- tiple processes concurrently, share resources among them, satisfy real–time constraints, etc. We, animals, do that all the time, and many machines do so as well. Only some of all those processes will be devoted to perception. But they should correspond to the goals and capacities of the system. In fact, they should be a part of them. The ASys perceptual framework is a general, unifying ap- proach, within which other perception theories may be anal- ysed. It starts from a formal notion of system, inherited from the Theory of General Systems (Klir, 1969). Hopefully, it will create a common theoretical background for natural and artificial systems upon which new bio-inspired engineering solutions can be developed. Studies of Perception The topic of perception has been studied from uncountable perspectives. Some explain aspects regarding specific phe- nomena, and some try to provide a global vision. Let us de- velop a brief overview. We could divide the studies of per- ception in three main categories. Many lines of research, both in natural and artificial per- ception, focus on low-level aspects, for example the biolog- ical structure of sensors and their electrochemical behaviour or research on signal processing. Examples of ongoing work in this trend are Bengtsson and Ull´en (2006) and Koelsch and Siebel (2005), which assess recognition of different aspects of auditory signals and neural correlates. Farah (2000) offers an overview of neural correlates across the different low and medium level perception processes. A second category of studies would concentrate on the pro- cess of perceiving actual objects in the environment. Exam- ples of this are Barth, La Mont, Lipton, and Spelke (2005), (Mandler, 2004), (Smith, Johnson, & Spelke, 2003) which assess object formation. Object perception is related to many other aspects of the observer system. Bodner and Lindsay (2003), Kensinger, Garoff-Eaton, and Schacter (2007) and Radvansky and Copeland (2006) explore memory retrieval in