Ebook: Plan-Based Control of Robotic Agents: Improving the Capabilities of Autonomous Robots
Author: Michael Beetz (eds.)
- Genre: Technique // Electronics: Robotics
- Tags: Artificial Intelligence (incl. Robotics), Computer Science general, Computer Communication Networks, Special Purpose and Application-Based Systems, Automation and Robotics, Control Engineering
- Series: Lecture Notes in Computer Science 2554 : Lecture Notes in Artificial Intelligence
- Year: 2002
- Publisher: Springer-Verlag Berlin Heidelberg
- City: Berlin; New York
- Edition: 1
- Language: English
- pdf
Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.
This book makes three major contributions to improving the capabilities of robotic agents:
- first, a plan representation method is introduced which allows for specifying flexible and reliable behavior
- second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans
- third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail.
Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.
This book makes three major contributions to improving the capabilities of robotic agents:
- first, a plan representation method is introduced which allows for specifying flexible and reliable behavior
- second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans
- third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail.