Towards a Robot Learning Architecture
نویسنده
چکیده
I summarize research toward a robot learning architecture intended to enable a mobile robot to learn a wide range of find-and-fetch tasks. In particular, this paper summarizes recent research in the Learning Robots Laboratory at Carnegie Mellon University on aspects of robot learning, and our current work toward integrating and extending this within a single architecture. In previous work we developed systems that learn action models for robot manipulation, learn cost-effective strategies for using sensors to approach and classify objects, learn models of sonar sensors for map building, learn reactive control strategies via reinforcement learning and compilation of action models, and explore effectively. Our current efforts aim to coalesce these disjoint approaches into a single robot learning agent that learns to construct action models in a real-world environment, learns models of visual and sonar sensors for object recognition and learns efficient reactive control strategies via reinforcement learning techniques utilizing these models.
منابع مشابه
An Unsupervised Learning Method for an Attacker Agent in Robot Soccer Competitions Based on the Kohonen Neural Network
RoboCup competition as a great test-bed, has turned to a worldwide popular domains in recent years. The main object of such competitions is to deal with complex behavior of systems whichconsist of multiple autonomous agents. The rich experience of human soccer player can be used as a valuable reference for a robot soccer player. However, because of the differences between real and simulated soc...
متن کاملRapid Reinforcement Learning for Reactive Control Policy Design in Autonomous Robots
This paper describes work in progress on a neural-based reinforcement learning architecture for the design of reactive control policies for an autonomous robot. Reinforcement learning techniques allow a programmer to specify the control program at the level of the desired behavior of the robot, rather than at the level of the program that generates the behavior. In this paper, we explicitly beg...
متن کاملA Q-learning Based Continuous Tuning of Fuzzy Wall Tracking
A simple easy to implement algorithm is proposed to address wall tracking task of an autonomous robot. The robot should navigate in unknown environments, find the nearest wall, and track it solely based on locally sensed data. The proposed method benefits from coupling fuzzy logic and Q-learning to meet requirements of autonomous navigations. Fuzzy if-then rules provide a reliable decision maki...
متن کاملDynamic Obstacle Avoidance by Distributed Algorithm based on Reinforcement Learning (RESEARCH NOTE)
In this paper we focus on the application of reinforcement learning to obstacle avoidance in dynamic Environments in wireless sensor networks. A distributed algorithm based on reinforcement learning is developed for sensor networks to guide mobile robot through the dynamic obstacles. The sensor network models the danger of the area under coverage as obstacles, and has the property of adoption o...
متن کاملOnline learning for object identification by a mobile robot
Object identification for a situated robot is a first step towards many relevant behaviours such as human-robot communication, object tracking, object detection, etc. However, the dynamic and unpredictable nature of the world makes it very difficult to design such algorithms. Our goal is to endow a Pioneer 2DX autonomous mobile robot with the ability to learn how to identify objects from its en...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2002