The Cognitive Robotic Systems Laboratory at AASS

(Previously "Mobile Robotics Lab")

Our Research Themes

PLEASE NOTE: This page has not been updated in a while. To get a glimpse of our current research topics and projects, please dowload our short Project Portfolio.

Scientific Framework
-> The scope of our investigation is not limited to traditional robots, but more generally to any intelligent system that is physically embedded in the environment through sensors and actuator. Mobile robots are instances of such systems, but simpler devices like intelligent home appliances or devices to interface with a human user also fit into this category.
-> PEIS We schematize a Physically Embedded Intelligent System (PEIS) as shown on the right. A system of this kind includes both cognitive functionalities that enable abstract reasoning (Modeling and Deliberation), and sensori-motoric functionalities that enable situatedness in the physical world (Perception and Control). Two assumptions underlie our otherwise general schema:
  • That the system is modular, that is, it is composed of a number of individual functional or behavioral components.
  • That the system is layered, that is, it consists of a cognitive layer and of a sensori-motoric layer.
-> We take inspiration from the fields of artificial intelligence and of robotics to realize the above two layers, respectively. Our aim, however, is not to perform incremental research in these two fields per-se, but to use knowledge and techniques from those fields to address the integration problem for a physically embedded intelligent system.
-> We address several facets of the integration problem. First, we study the integration within a single PEIS -- namely, between the high-level cognitive functionalities (M, D) and the low-level sensori-motoric ones (P, C). Second, we study the integration across multiple PEIS -- how to make multiple PEIS cooperate during the performance of tasks. Finally, we study the integration of (single and multiple) PEIS with the environment, e.g. using non-standard sensor modalities like olfaction, and with the humans who inhabit the environment.
-> The above facets are reflected in our four broad research themes: Cognitive robots, Robot ecologies, Artificial olfaction, and Robots for the humans.
Theme 1: Cognitive Robots
-> A physically embedded intelligent system reasons about the pysical world which it is embedded in. Deliberation is needed to connect its contingent actions to its global goals and long-term desires. To be effective, the knowledge on which deliberations are based must be consistent with the physical world; symmetrically, the results of deliberation must be correctly translated into physical actions. In other words, the system must make sure that its conitive processes are in sync with the physical world. The general question addressed in this research theme is how the above syncronization can be achieved. This question is central to our ability to realize cognitive robots, that is, systems that can both interact with the physical world and reason about it. In our generic PEIS agent, this question translates in how to realize the links between the cognitive functionalities (M+D) and the sensori-motoric functionalities (P+C).
-> Anchoring The first part of the above question is how to connect knowledge-based models (M) with perception (P). Symbolic names, like cup-22, are used to denote objects in most AI reasoning and planning systems. When the robot must physically access these objects, however, it must rely on the data provided by its sensors. For instance, to perform the action Pickup(cup-22), a robot must use the data provided by its camera about the position and shape of the cup. We call perceptual anchoring the problem to create, and to maintain in time, the connection between symbols and sensor data that refer to the same physical objects. Perceptual anchoring is closely related to the symbol grounding problem, one of the fundamental problems in artificial intelligence, but it addresses a specific case: one in which the symbols refer to physical objects. Our objective within this research theme is to provide practical solutions to the anchoring problem, despite of its philosophical complexities. To be practical, these solutions must also adress problems like observation failures, sensor uncertainty, and perceptual ambiguity.
-> Plan execution The second part of the above question is how to connect goal-oriented deliberation (D) with control and reactive execution (C). The field of AI has witnessed impressive development in the design of knowledge-based planners able to deal with complex tasks in an efficient way. The generated plans often assume that the executing system can reliably execute abstract actions, and that it can correctly estimate the current state of the world. Physical perception and execution, however, are inherently uncertain and may fail, especially in a dynamic world. Our objective within this research theme is to develop planning techniques that can be used to guide reactive behavior in the presence of uncertainty and dynamicity. The generated plans must include provisions for reacting to new perceived information, as well as for acquiring this information when needed. An interesting case is when dynamicity and uncertainty are introduced by the presence of humans in the environment where the robot operates.
-> This research theme is currently reflected in the following concrete projects:
Theme 2: Robot Ecologies
-> Robot Ecology In addition to studying physically embedded intelligent systems in isolation, we are interested in studying collections of such systems. In this research theme, we take an ecological viewpoint in which the robots and the environment are seen as parts of the same system. Robots can be pervasively distributed throughout the environment in the form of mobile platforms, embedded sensors, actuators, or smart objects, and they can engage in symbiotic relationships. This research theme is devoted to study how robot ecologies of this type can collectively perform tasks. The general paradigm that we adopt is that each physically embedded intelligent system in the ecology can "borrow" functionalities from other systems in order to compensate or complement its own. Alternatively, one could say that we consider an overall physically embedded intelligent system whose components are distributed among a set of separated physical entities.
-> This research theme naturally interacts with the other themes. In particular, we are interested to investigate how a cognitive robot can be realized in a distributed way, and how to deal with perceptual anchoring and of plan execution in the distributed case. We also investigate robot ecologies capable of olfaction and robot ecologies that include humans, especially in the context of elderly care in domestic environments.
-> This research theme is currently reflected in the following concrete projects:
Theme 3: Artificial Olfaction
-> We have a special interest in a sensor modality which has been scarsely used in robotic applications until now: olfaction. In this research line we study techniques for artificial olfaction, and their integration within an intelligent robotic system. This research line has strong interactions with the other lines: these include the integration of olfaction with knowledge and cognition, the enrichment of a robot ecology with olfaction, and the use of olfaction in medical applications.
-> This research theme is currently reflected in the following concrete projects:
Theme 4: Robots for Humans
-> Robot for humans In this research theme, we investigate the use of robotic technologies to improve the quality of life of humans. We are especially interested in the applications of robotic technologies to health care, with special emphasis on the elderly population. Robotic technologies are intended here in a broad sense, including for instance sensing and sensor interpretation. Our approach in this research theme is highly interdisciplinary: we work closely with researchers from other relevant disciplines, like medicine, psychology, and nursery; with social actors involved in organizing or delivering elderly care; with economic actors involved in the creation of relevant products; and with end users like patients or elderly people.
-> This research theme is currently reflected in the following concrete projects:

Last updated on Nov 13, 2009 by A. Saffiotti