Konolige, Kurt


The Revisiting Problem in Mobile Robot Map Building: A Hierarchical Bayesian Approach

arXiv.org Artificial Intelligence

We present an application of hierarchical Bayesian estimation to robot map building. The revisiting problem occurs when a robot has to decide whether it is seeing a previously-built portion of a map, or is exploring new territory. This is a difficult decision problem, requiring the probability of being outside of the current known map. To estimate this probability, we model the structure of a "typical" environment as a hidden Markov model that generates sequences of views observed by a robot navigating through the environment. A Dirichlet prior over structural models is learned from previously explored environments. Whenever a robot explores a new environment, the posterior over the model is estimated by Dirichlet hyperparameters. Our approach is implemented and tested in the context of multi-robot map merging, a particularly difficult instance of the revisiting problem. Experiments with robot data show that the technique yields strong improvements over alternative methods.


Many Robots Make Short Work: Report of the SRI International Mobile Robot Team

AI Magazine

Indoor mobile robots are becoming reliable enough in navigation tasks to consider working with teams of robots. Using SRI International's open-agent architecture (OAA) and SAPHIRA robot-control system, we configured three physical robots and a set of software agents on the internet to plan and act in coordination. Users communicate with the robots using a variety of multimodal input: pen, voice, and keyboard. The robust capabilities of the OAA and SAPHIRA enabled us to design and implement a winning team in the six weeks before the Fifth Annual AAAI Mobile Robot Competition and Exhibition.


Many Robots Make Short Work: Report of the SRI International Mobile Robot Team

AI Magazine

Indoor mobile robots are becoming reliable enough in navigation tasks to consider working with teams of robots. Using SRI International's open-agent architecture (OAA) and SAPHIRA robot-control system, we configured three physical robots and a set of software agents on the internet to plan and act in coordination. Users communicate with the robots using a variety of multimodal input: pen, voice, and keyboard. The robust capabilities of the OAA and SAPHIRA enabled us to design and implement a winning team in the six weeks before the Fifth Annual AAAI Mobile Robot Competition and Exhibition.


ERRATIC Competes with the Big Boys

AI Magazine

I detail the robot's history and describe the perceptual and control architecture. The success of the robot is highlighted in a description of the robot's performance during the competition.


ERRATIC Competes with the Big Boys

AI Magazine

This article discusses the development of the robot erratic, the second-place winner of the 1994 AAAI Robot Competition and Exhibition. I detail the robot's history and describe the perceptual and control architecture. The success of the robot is highlighted in a description of the robot's performance during the competition.


Designing the 1993 Robot Competition

AI Magazine

The Second Annual Robotics Competition and Exhibition was held in July 1993 in conjunction with the National Conference on Artificial Intelligence. This article reports some of my experiences in helping to design and run the contest and some reflections, drawn from post mortem abstracts written by the competitors, on the relation of the contest to current research efforts in mobile robotics.


Designing the 1993 Robot Competition

AI Magazine

The Second Annual Robotics Competition and Exhibition was held in July 1993 in conjunction with the National Conference on Artificial Intelligence. This article reports some of my experiences in helping to design and run the contest and some reflections, drawn from post mortem abstracts written by the competitors, on the relation of the contest to current research efforts in mobile robotics.


Carmel Versus Flakey: A Comparison of Two Winners

AI Magazine

The University of Michigan's CARMEL and SRI International's FLAKEY were the first- and second-place finishers, respectively, at the 1992 Robot Competition sponsored by the Association for the Advancement of Artificial Intelligence. The two teams used vastly different approaches in the design of their robots. Many of these differences were for technical reasons, although time constraints, financial resources, and long-term research objectives also played a part. This article gives a technical comparison of CARMEL and FLAKEY, focusing on design issues that were not directly reflected in the scoring criteria.


Carmel Versus Flakey: A Comparison of Two Winners

AI Magazine

The University of Michigan's CARMEL and SRI International's FLAKEY were the first- and second-place finishers, respectively, at the 1992 Robot Competition sponsored by the Association for the Advancement of Artificial Intelligence. The two teams used vastly different approaches in the design of their robots. Many of these differences were for technical reasons, although time constraints, financial resources, and long-term research objectives also played a part. This article gives a technical comparison of CARMEL and FLAKEY, focusing on design issues that were not directly reflected in the scoring criteria.