In an attempt to solve as much of the AAAI Robot Challenge as possible, five research institutions representing academia, industry, and government integrated their research into a single robot named GRACE This article describes this first-year effort by the GRACE team, including not only the various techniques each participant brought to GRACE but also the difficult integration effort itself

GRACE: An Autonomous Robot for the AAAI Robot Challenge.

In an attempt to solve as much of the AAAI Robot Challenge as possible, five research institutions representing academia, industry, and government integrated their research into a single robot named GRACE. This article describes this first-year effort by the GRACE team, including not only the various techniques each participant brought to GRACE but also the difficult integration effort itself.

/pdf/grace-an-autonomous-robot-for-the-aaai-robot-challenge-5mckzk34du.pdf

GRACE: an autonomous robot for the AAAI Robot challenge

Building autonomous systems that achieve human level intelligence is one of the primary objectives in artificial intelligence (AI). It requires the study of a wide range of functions robustly across different phases of human cognition. This paper presents a review of agent cognitive architectures in the past 20 year’s AI research. Different from software structures and simulation environments, most of the architectures concerned are established from mathematics and philosophy. They are categorized according to their knowledge processing patterns—symbolic, emergent or hybrid. All the relevant literature can be accessed publicly, particularly through the Internet. Available websites are also summarized for further reference.

A Survey of Cognitive Architectures in the Past 20 Years

We present a methodology for designing and implementing interactive intelligences. The constructionist design methodology (CDM) -- so called because it advocates modular building blocks and incorporation of prior work -- addresses factors that we see as key to future advances in AI, including support for interdisciplinary collaboration, coordination of teams, and large-scale systems integration. We test the methodology by building an interactive multifunctional system with a real-time perception- action loop. The system, whose construction relied entirely on the methodology, consists of an embodied virtual agent that can perceive both real and virtual objects in an augmented-reality room and interact with a user through coordinated gestures and speech. Wireless tracking technologies give the agent awareness of the environment and the user's speech and communicative acts. User and agent can communicate about things in the environment, their placement, and their function, as well as about more abstract topics, such as current news, through situated multimodal dialogue. The results demonstrate the CDM's strength in simplifying the modeling of complex, multifunctional systems that require architectural experimentation and exploration of unclear subsystem boundaries, undefined variables, and tangled data flow and control hierarchies.

/pdf/constructionist-design-methodology-for-interactive-kmlhg0xz2p.pdf

Constructionist Design Methodology for Interactive Intelligences

Computer Vision Systems

This article describes the winning entries in the 2000 Association for the Advancement of Artificial Intelligence Mobile Robot Competition. The robots, developed by Swarthmore College, all used a modular hybrid architecture designed to enable reflexive responses to perceptual input. Within this architecture, the robots integrated visual sensing, speech synthesis and recognition, the display of an animated face, navigation, and interrobot communication. In the Hors d'Oeuvres, Anyone? event, a team of robots entertained the crowd while they interactively served cookies; and in the Urban Search-and-Rescue event, a single robot autonomously explored a section of the test area, identified interesting features, built an annotated map, and exited the test area within the allotted time.

/pdf/reaper-a-reflexive-architecture-for-perceptive-agents-1f19t5sxuy.pdf

REAPER: A Reflexive Architecture for Perceptive Agents

. Interactive robotics demands real-time visual information about the environment. Real-time vision processing, however, places a heavy load on the robot's limited resources, which must accommodate multiple other processes running simultaneously. This paper describes a vision module capable of providing real-time information from ten or more operators while maintaining at least a 20-Hz frame rate and leaving sufficient processor time for a robot's other capabilities. The vision module uses a probabilistic scheduling algorithm to ensure both timely information flow and a fast frame capture. In addition, it tightly integrates the vision operators with control of a pan-tilt-zoom camera. The vision module makes its information available to other modules in the robot architecture through a shared memory structure. The information provided by the vision module includes the operator information along with a time stamp indicating information relevance. Because of this design, our robots are able to react in a timely manner to a wide variety of visual events.

https://www.cs.colby.edu/maxwell/papers/pdfs/Maxwell+etal-ICVS-2001.pdf

A real-time vision module for interactive perceptual agents

Interactive robotics demands real-time visual information about the environment. Real time vision processing, however, places a heavy load on the robot's limited resources, and must accommodate other processes such as speech recognition, animated face displays, communication with other robots, navigation and control. For our entries in the 2000 American Association for Artificial Intelligence robot contest, we developed a vision module capable of providing real-time information about ten or more operators while maintaining at least a 20Hz frame rate and leaving sufficient processor time for the robot's other capabilities. The vision module uses a probabilistic scheduling algorithm to ensure both timely information flow and a fast frame capture. The vision module makes its information available to other modules in the robot architecture through a shared memory structure. The information provided by the vision module includes the operator information along with a confidence measure and a time stamp. Because of this design, our robots are able to react in a timely manner to a wide variety of visual events.

A Real-Time Vision Module for Interactive Perceptual Agents

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REAPER: A Reflexive Architecture for Perceptive Agents

A real-time vision module for interactive perceptual agents

A Real-Time Vision Module for Interactive Perceptual Agents