Cognitive Robotics

Learning an approximate map of the environment by unsupervised bimodal landmark exploration

by Lambert Schomaker

Lambert Schomaker and Rudolf Fehrmann

Technological methods for navigation have achieved a high level of perfection, currently. However, this perfection is... more Technological methods for navigation have achieved a high level of perfection, currently. However, this perfection is mostly achieved at the cost of additional artificial equipment which is extraneous to a freely-navigating agent such as an autonomous robot. Cognitive, biological navigation is based on functionality which is intrinsic to the cognitive system and thus more flexible and autonomous in the true sense. In this paper, exploratory experiments in navigation are performed, based on proximity events, visual landmarks, and distances traveled (odometry). It will be shown that a robot is able to learn a Kohonen self-organized landmark map of image and sonar data. An approximate 2-D map of the environment can be computed on the basis of the two major principal components within a sparse distance matrix between landmarks.

Birth of the object: Detection of objectness and extraction of object shape through object action complexes

by Nicolas Pugeault

CoEvolutionary Approaches in Cognitive Robotic System Design

by michail Maniadakis

Using Robotic Competitions in Undergraduate Philosophy Courses: Studying the Mind Through Simple Robotics

by John Sullins

Presented at AAAI workshop on educational robotics

Robotic competitions can add a great deal to undergraduate
philosophy courses. I have successfully used Legomore Robotic competitions can add a great deal to undergraduate
philosophy courses. I have successfully used Lego
MindStorms kits in this manner to teach; logic, philosophy
of AI, philosophy and cognitive robotics, and issues in the
philosophy of technology. The following presentation will
describe some of my hard won experience in finding the
best ways to cheaply and efficiently introduce robotic
competition activities into the classroom, which will be of
interest to any educators regardless of their disciplines.

The basis of shared intentions in human and robot cognition

by Felix Warneken

Co-authored with P. F. Dominey
Published in 'New Ideas in Psychology' 2009

There is a fundamental difference between robots that are equipped with sensory, motor and cognitive capabilities, vs.... more There is a fundamental difference between robots that are equipped with sensory, motor and cognitive capabilities, vs. simulations or non-embodied cognitive systems. Via their perceptual and motor capabilities, these robotic systems can interact with humans in an increasingly more “natural” way, physically interacting with shared objects in cooperative action settings. Indeed, such cognitive robotic systems provide a unique opportunity to developmental psychologists for implementing their theories and testing their hypotheses on systems that are becoming increasingly “at home” in the sensory--motor and social worlds, where such hypotheses are relevant. The current research is the result of interaction between research in computational neuroscience and robotics on the one hand, and developmental psychology on the other. One of the key findings in the developmental psychology context is that with respect to other primates, humans appear to have a unique ability and motivation to share goals and intentions with others. This ability is expressed in cooperative behavior very early in life, and appears to be the basis for subsequent development of social cognition. Here we attempt to identify a set of core functional elements of cooperative behavior and the corresponding shared intentional representations. We then begin to specify how these capabilities can be implemented in a robotic system, the Cooperator, and tested in human–robot interaction experiments. Based on the results of these experiments we discuss the mutual benefit for both fields of the interaction between robotics and developmental psychology.

How long is a moment: The perception and reality of task-related absences

by Bill Kennedy

published in the International Journal of Social Robotics

We have investigated actual and perceived human performance associated with a simple task involving walking and... more We have investigated actual and perceived human performance associated with a simple task involving walking and applied the developed knowledge to a human-robot interaction. Based on experiments involving walking at a “purposeful and comfortable” pace, parameters were determined for a trapezoidal model of walking: starting from standing still, accelerating to a constant pace, walking at a constant pace, and decelerating to a stop. We also collected data on humans’ evaluation of the accomplishment of a simple task involving walking: determining the transitions from having taken too short a period of time to an appropriate time and from having taken an appropriate time to having taken too long. People were found to be accurate in estimating the task duration for short tasks, but to underestimate the duration of longer tasks. This information was applied to a human-robot interaction involving a human leaving for a “moment” and the robot knows how long the task should take and how time is evaluated by a human.

Context in Cognitive Robotics

by Michael Gratton

A Reasoning Module for Long-Lived Cognitive Agents (PhD 2009)

by Stavros Vassos

Ph.D. Thesis, University of Toronto Computer Science Department, Toronto, Canada, Supervisor: Hector J. Levesque, 2009.

In this thesis we study a reasoning module for agents that have cognitive abilities, such as memory, perception,... more In this thesis we study a reasoning module for agents that have cognitive abilities, such as memory, perception, action, and are expected to function autonomously for long periods of time. The module provides the ability to reason about action and change using the language of the situation calculus and variants of the basic action theories. The main focus of this thesis is on the logical problem of progressing an action theory.
First, we investigate the conjecture by Lin and Reiter that a practical first-order definition of progression is not appropriate for the general case. We show that Lin and Reiter were indeed correct in their intuitions by providing a proof for the conjecture, thus resolving the open question about the first-order definability of progression and justifying the need for a second-order definition.
Then we proceed to identify three cases where it is possible to obtain a first-order progression with the desired properties: i) we extend earlier work by Lin and Reiter and present a case where we restrict our attention to a practical class of queries that may only quantify over situations in a limited way; ii) we revisit the local-effect assumption of Liu and Levesque that requires that the effects of an action are fixed by the arguments of the action and show that in this case a first-order progression is suitable; iii) we investigate a way that the local-effect assumption can be relaxed and show that when the initial knowledge base is a database of possible closures and the effects of the actions are range-restricted then a first-order progression is also suitable under a just-in-time assumption.
Finally, we examine a special case of the action theories with range-restricted effects and present an algorithm for computing a finite progression. We prove the correctness and the complexity of the algorithm, and show its application in a simple example that is inspired by video games.

Obstacle avoidance as a consequence of suppressing irreversible actions

by Adam Eppendahl

ICRA 2007 Proceedings

Efficient Epistemic Reasoning in Partially Observable Dynamic Domains Using Hidden Causal Dependencies

by Theodore Patkos

Reasoning with knowledge, action and time in dynamic and uncertain domains

by Theodore Patkos

Grounded situation models for robots: Bridging language, perception, and action

by Nikolaos Mavridis

Co-authored with: N. Mavridis, D. Roy, Published in Proceedings of the Conference of the American Artificial Intellegince Association AAAI-05 Work shop on Modular Construction of Human-Like Intelligence, http://www.aaai.org/Library/Workshops/2005/ws05-08-006.php

Our long-term objective is to develop robots that engage in natural language-mediated cooperative tasks with humans.... more Our long-term objective is to develop robots that engage in natural language-mediated cooperative tasks with humans. To support this goal, we are developing an amodal representation called a grounded situation model (GSM), as well as a modular architecture in which the GSM resides in a centrally located module. We present an implemented system that allows of a range of conversational and assistive behavior by a manipulator robot. The robot updates beliefs about its physical environment and body, based on a mixture of linguistic, visual and proprioceptive evidence. It can answer basic questions about the present or past and also perform actions through verbal interaction. Most importantly, a novel contribution of our approach is the robot’s ability for seamless integration of both language and sensor-derived information about the situation: For
example, the system can acquire parts of situations either by seeing them or by “imagining” them through descriptions given by the user: “There is a red ball at the left”. These situations can later be used to create mental imagery, thus enabling bidirectional translation between perception and language. This work constitutes a step towards robots that use situated natural language grounded in perception and action.

Conversational robots: Building blocks for grounding word meaning

by Nikolaos Mavridis

Co-authored with: D. Roy, K. Hsiao. Published in Proceedings of the HLT-NAACL03 Workshop on Learning Word Meaning from Non-Linguistic Data, http://dl.acm.org/citation.cfm?id=1119222

How can we build robots that engage in fluid spoken conversations with people, moving beyond canned responses to words... more How can we build robots that engage in fluid spoken conversations with people, moving beyond canned responses to words and towards actually understanding? As a step towards addressing this question, we introduce a robotic architecture that provides a basis for grounding word meanings. The architecture provides perceptual, procedural, and affordance representations for grounding words. A perceptually coupled on-line simulator enables sensorymotor representations that can shift points of view. Held together, we show that this architecture provides a rich set of data structures and procedures that provide the foundations for grounding the meaning of certain classes of words.

Grounded situation models for situated conversational assistants

by Nikolaos Mavridis

MIT PhD Thesis, http://dspace.mit.edu/handle/1721.1/38523, for printable version press Green "Download" button below

A Situated Conversational Assistant (SCA) is any system with sensing, acting and speech abilities, which engages in... more A Situated Conversational Assistant (SCA) is any system with sensing, acting and speech abilities, which engages in physically situated natural language conversation with human partners and assists them in tasks. Towards such assistants, a computational model of embodied agents is presented, which produces systems that are capable of a core set of situated natural language skills, and which provides concrete leverage for numerous extensions. The central idea is to endow agents with a sensor-updated set of structures and processes called a Grounded Situation Model (GSM), which is closely related to the cognitive psychology notion of situation models. The GSM contains descriptions of physical & mental aspects of past, current, or imagined situations, enabling bidirectional translation between linguistic descriptions and perceptual data/expectations. The power of the GSM proposal is demonstrated through the real-world example of a manipulator robot with speech and vision, with abilities comparable to those required by a normally- developing child in order to pass the Token Test, a standard psychological test for three-year old children.

Coupling perception and simulation: Steps towards conversational robotics

by Nikolaos Mavridis

Co-authored with: D. Roy, K. Hsiao, Published in Proceedings of the IEEE IROS'2003 conference, http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=1250747

Human cognition makes extensive use of visualization and imagination. As a first step towards giving a robot similar... more Human cognition makes extensive use of visualization and imagination. As a first step towards giving a robot similar abilities, we have built a robotic system that uses a perceptually-coupled physical simulator to produce an internal world model of the robot’s environment. Real-time perceptual coupling ensures that the model is constantly kept in synchronization with the physical environment as the robot moves and obtains new sense data. This model allows the robot to be aware of objects no longer in its field of view (a form of “object permanence”), as well as to visualize its environment through the eyes of the user by enabling virtual shifts in point of view using synthetic vision operating within the simulator. This architecture provides a basis for our long term goals of developing conversational robots that can ground the meaning of spoken language in terms of sensorimotor representations.

Construct to Understand: Learning Through Exploration

by Zoe Demery

Demery, Z., Rios, V. E. A., Sloman, A., Wyatt, J., & Chappell, J. (2010). Construct to Understand : Learning through Exploration. In Proceedings of the International Symposium on AI-Inspired Biology (pp. 59–61). Presented at the Proceedings of the International Symposium on AI-Inspired Biology.

Artificial Intelligence (AI) and Animal Cognition(AC) share a common goal: to study learning and causal understanding.... more Artificial Intelligence (AI) and Animal Cognition(AC) share a common goal: to study learning and causal understanding. However, the perspectives are completely different: while AC studies intelligent systems present in nature, AI tries to to build them almost from scratch. It is proposed here that both visions are complementary and should interact more to better achieve their ends. Nonetheless, before efficient collaboration can take place, a greater mutual understanding ofeach field is required, beginning with clarifications of their respective terminologies and considering the constraints of the research in each field.

Tekkotsu: Cognitive Robotics on the Sony AIBO

by Jordan Wales

by Ethan J. Tira-Thompson, Neil S. Halelamien, Jordan J. Wales, David S. Touretzky. Proceedings of the 2004 International Conference on Cognitive Modeling.

Cognitive Primitives for Mobile Robots

by Jordan Wales

by Ethan Tira-Thompson, N.S. Halelamien, J.J. Wales, and David S. Touretzky. AAAI 2004 Fall Symposium Series, “The Intersection of Cognitive Science and Robotics: From Interfaces to Intelligence,” Report FS-04-05 (2004): 110–111.

Dual-Coding Representations for Robot Vision Programming in Tekkotsu

by Jordan Wales

by David. S. Touretzky, Neil. S. Halelamien, Jordan. J. Wales. Autonomous Robots 22:4 (2007): 425–435.

The Task Matrix: An Extensible Framework for Creating Versatile Humanoid Robots

by Victor Ng-Thow-Hing

Evan Drumwright and Victor Ng-Thow-Hing. "The Task Matrix: An Extensible Framework for Creating Versatile Humanoid Robots". Proc. of the IEEE Intl. Conf. on Robotics and Automation (ICRA). Orlando, FL. 2006.

The successful acquisition and organization of a large number of skills for humanoid robots can be facilitated with a... more The successful acquisition and organization of a large number of skills for humanoid robots can be facilitated with a collection of performable tasks organized in a task matrix. Tasks in the matrix can utilize particular preconditions and inconditions to enable execution, motion trajectories to specify desired movement, and references to other tasks to perform subtasks. Interaction between the matrix and external modules such as goal planners is achieved via a high-level interface that categorizes a task using its semantics and execution parameters, allowing queries on the matrix to be performed using different selection criteria. Performable tasks are stored in an XML-based file format that can be readily edited and processed by other applications. In its current implementation, the matrix is populated with sets of primitive tasks (eg., reaching, grasping, arm-waving) and macro tasks that reference multiple primitive tasks (Pick-and-place and Facing-and-waving).