The Crucial Role of Robot Self-Awareness in HRI Manuel Birlo Adriana Tapus Cognitive Robotics Lab/UEI Cognitive Robotics Lab/UEI ENSTA-ParisTech ENSTA-ParisTech 32 Blvd Victor, 75015, Paris, France 32 Blvd Victor, 75015, Paris, France email@example.com firstname.lastname@example.org ABSTRACT In this paper, we present the ﬁrst steps towards a new con- cept of robot self-awareness that can be implemented into embodied robot systems. Our concept of “the self” is inspired by already existing approaches and aims to provide a cog- nitive system with meta-cognitive capabilities. We believe that robot self-awareness is a crucial factor in the improve- ment of HRI. Categories and Subject Descriptors H.1.2 [Information Systems]: Models and Principles— User/Machine Systems (a) (b) General Terms Theory Figure 1: Our approach: (a) self concept and (b) perspective taking 1. INTRODUCTION Recent developments in the ﬁeld of Human-Robot Interac- thors in  consider a robot to be self-aware if it has the tion(HRI) aim to focus on tasks that require more and more ability to focus attention to the representation of its inter- robotic cognition capabilities. However, given the fact that nal states. They have created a framework called ASMO a human has an inﬁnite number of possible interaction capa- and showed ﬁrst results by using a small humanoid robot in bilities as well as an inﬁnite set of desires and needs, current a simple interaction scenario. In their approach, the robot solutions in terms of robot’s cognition capabilities look quite has the ability to deliberate and re-plan its behavior based poor. None of the existing cognitive architectures are ade- on its intentions and its concept of “the self”. However, quate for complex and dynamic environments in which the as far as we know, they tested their approach only for a robot has the capability to take an inﬁnite number of possi- speciﬁc application whose interaction possibilities are quite ble human-sided actions and behaviors as well as dynamical limited. Another approach was presented in . The pre- environment changes into account. sented architecture which is called GMU BICA follows a Let’s imagine a system that’s aware of itself and thus able concept called schema that represents concepts in one uni- to monitor its own capabilities and limitations. Such a sys- versal format. Their work has been validated only in simula- tem should also recognize situations in which its own capa- tion. Furthermore, a promising approach named ACT-R/E bilities are not suitable for unforseen environmental changes (ACT-R/Embodied, an extension of ACT-R ) has been and, as a consequence, adapt its own code in order to be described in . Based upon the existing cognitive architec- able to handle those new situations. Therefore, a system ture ACT-R , the authors have developed modules that that is self-aware could theoretically be able to overcome are able to deal with real word information such as vision current limitations of applications comprising a ﬁnite num- and sound. Nevertheless, to the best of our knowledge, there ber of foreseen inputs and corresponding outputs. This is is no concept of self-awareness in the sense of having a sys- the main focus of this paper. tem acting on a meta-level that is able to deliberate and re-plan its performance according to its intentions and self- 2. RELATED WORK conception. There is no unique deﬁnition of self-awareness and of the way it could be transposed in robot’s behavior. The au- 3. METHOLOGY Our approach of robot self-awareness has the concept of meta-cognition in common with the work of  and  (i.e., Copyright is held by the author/owner(s). HRI’11, March 6–9, 2011, Lausanne, Switzerland. it was proven in the psychological and behavioral literature ACM 978-1-4503-0561-7/11/03. that human self-awareness is something that happens on a module determines the content of its self buﬀer. The con- tent of the self buﬀer represents the focus of the system’s attention on a meta-level. By having all the other buﬀer contents as well as ACT-R/E’s current focus of attention (represented by its focus buﬀer) “in mind”, the self is able to interfere about what’s happening inside ACT-R/E’s proce- dural module. The procedural module termines the system’s behavior and sets the current focus of attention (the focus buﬀer). As the self module has the capability to interfere in the processeses of the procedural it is able to deliberate and re-plan ACT-R/E’s behavior; this corresponds to our previous explained conception of self-awareness. Figure 2: Combination of the ACT-R/E architecture and our self module (ﬁgure of ACT-R/E architecture is taken 4. EXPERIMENTAL DESIGN from http://newhri.org/Presentations/trafton newhri.pdf) In order to test our approach we plan on using the NAO humanoid robot from Aldebaran Robotics and Python ACT- R from Carleton Cognitive Modelling Lab (http://ccmsuite. meta-level). Our work also focuses on the representation of ccmlab.ca/). As a ﬁrst testing environment, we create a internal states since a simple interaction between the robot’s small interaction scenario in which the human and the robot external states in terms of in- and outputs via the external are sitting in front of each other at a table (see Fig.1b). The world is not suﬃcient in order for the robot to be able to act aim of this scenario is to enable the robot to take the per- self-aware. The robot has to create its own interpretation of spective of the human in order to understand verbal com- what it perceives and it has to connect this information to mands that are ambiguous correctly. As the ability of per- its current internal state as well as to its previous states. spective taking leads to advanced human-robot interaction The main question here is how to create a concept for , it is a good example to test our self concept. Fig.1b these internal representations and a meta-cognition and how shows a table with two balls and a wall. One of the balls to use it with a humanoid robot. The ACT-R architecture is hidden by a wall from the human’s perspective while the  that aim to model cognitive features of the human brain robot can see both of them. When the human ask the robot is used as a foundation for our approach. We use the chunk “Give me that ball” this command is ambiguous at a ﬁrst and production based concept of ACT-R as a ﬁrst step to- glance since the robot doesn’t know which ball the human is wards self-awareness within a humanoid robot as ACT-R speaking about because there a two identical balls. However, oﬀers a quite easy way to use general concepts that are in- if the robot is able to take the perspective of the human it spired by the human brain. Buﬀers in ACT-R represent the will automatically know that the human can only see one ball current focus of attention of a human brain, and they can be and therefore, it will know which ball the user is referring connected to a memory. Let’s imagine a human that thinks to. We try to achieve this goal by using our meta-cognition about something that he perceives right now; this informa- concept. This is work is on progress and some preliminary tion is stored in his “buﬀer”. If he thinks about something results will be available by the time of the conference. right now that is connected to an experience in the past, he has to recall information from his memory. This corre- 5. CONCLUSION sponds to ACT-R buﬀers that are connected to memories. Our current aim is to create a concept of self-awareness We propose to represent a mental state as a chunk (i.e., a in a humanoid robot based on the existing ACT-R cognitive string) that consists of all the required information about architecture. To this end, we try to develop an approach the robot’s perception, internal state, and connections to of meta-cognition that is able to deliberate and re-plan the previous states in an abstract way. This also requires an ap- robot’s behavior by focusing on representations of mental proach that reduces the real world perception of the robot, states while using the chunk system of ACT-R. In our future for example its vision and speech recognition, to abstract in- work, we will try to implement more complex HRI scenarios formation inside its internal world (see Fig.1a). Abstraction that focus on important needs within HRI. is neccessary because the chuck system in ACT-R allows only a rather simple way to store information. Meta-cognition, which represents the self, is instantiated as an independent 6. REFERENCES  J. R. Anderson. ACT-R ACT-R Research Group, unit that looks over all buﬀers and memory contents and CMU, http://act-r.psy.cmu.edu. decides on which of these buﬀers it will pay attention to. Finally, our concept of robot self-awareness looks like in  R. Novianto and M.-A. Williams. The role of attention Fig.2 that shows a combination of the ACT-R/E architec- in robot self-awareness. In Proc. RO-MAN 2009, ture and our self-module (in red). Our self module has access Toyama, Japan, 2009. to every module and buﬀer of ACT-R/E so as to be able to  A. Samsonovich. Universal learner as an embryo of “be aware of” everything that is happening in the robot’s computational consciousness. In Association for the “brain”. On one hand, access to the ACT-R/E modules is Advancement of Artiﬁcial Intelligence, 2007. required in order for “the self” to retrieve information about  J. G. Trafton, N. L. Cassimatis, M. D. Bugajska, D. P. memories and possible actions, and on the other hand, access Brock, F. E. Mintz, and A. C. Schultz. Enabling to the ACT-R/E buﬀers is neccessary since the self should eﬀective human-robot interaction using be able to be aware of what’s currently inside the robot’s perspective-taking in robots. IEEE Transactions on working memory. Based on all this information, the self Systems, Man, and Cybernetics, 35(4):460–470, 2005.
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