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Using Genetic Algorithms to Learn Reactive Control Parameters for Autonomous Robotic Navigation
(Georgia Institute of Technology, 1994)
This paper explores the application of genetic algorithms to the learning of local robot navigation behaviors for reactive control systems. Our approach evolves reactive control systems in various environments, thus creating ...
Io, Ganymede and Callisto - a Multiagent Robot Trash-Collecting Team
(Georgia Institute of Technology, 1995)
Georgia Tech won the Office Cleanup Event at the 1994 AAAI Mobile Robot Competition with a multi-robot cooperating team. This paper describes the design and implementation of these reactive trash-collecting robots, including ...
Behavioral Models of the Praying Mantis as a Basis for Robotic Behavior
(Georgia Institute of Technology, 1999)
Formal models of animal sensorimotor behavior can provide effective methods
for generating robotic intelligence. In this article we describe how schema-theoretic
models of the praying mantis derived from behavioral and ...
A Neural Schema Architecture for Autonomous Robots
(Georgia Institute of Technology, 1998)
As autonomous robots become more complex in their behavior, more sophisticated software
architectures are required to support the ever more sophisticated robotics software. These
software architectures must support complex ...
Using the CONDENSATION Algorithm for Robust, Vision-Based Mobile Robot Localization
(Georgia Institute of Technology, 1999)
To navigate reliably in indoor environments, a mobile
robot must know where it is. This includes both the ability
of globally localizing the robot from scratch, as well
as tracking the robot’s position once its location ...
Perceptual Support for Ballistic Motion in Docking for a Mobile Robot
(Georgia Institute of Technology, 1991)
This paper describes ongoing research into methods to allow a mobile robot to effectively function in a manufacturing environment; specifically, generation of the ballistic motion phase of the docking behavior. This overall ...
Experiments With Reinforcement Learning in Problems With Continuous State and Action Spaces
(Georgia Institute of Technology, 1996)
A key element in the solution of reinforcement learning problems is the value function. The purpose of this function is to measure the long-term utility or value of any given state and it is important because an agent can ...
Model-Based Reconfiguration of Schema-Based Reactive Control Architectures
(Georgia Institute of Technology, 1997)
Reactive methods of control get caught in local minima. Fortunately schema-based reactive control systems have built-in redundancy that enables multiple configurations with different modes. We describe a model-based method ...
Development of Visual Tracking Algorithms for an Autonomous Helicopter
(Georgia Institute of Technology, 1995)
A visual target designation and tracking system is being developed within the context of the Autonomous Scout Rotorcraft Testbed Project at Georgia Tech. This paper describes both the algorithms and the hardware being used ...
Visualization of Multi-Level Neural-Based Robotic Systems
(Georgia Institute of Technology, 1998)
Autonomous biological systems are very complex in their nature. Their study, through both experimentation and computation, provides a means to understand the underlying mechanisms in living systems while inspiring the ...