Journal Information
Autonomous Robots
http://www.springer.com/engineering/robotics/journal/10514
Impact Factor:
3.000
Publisher:
Springer
ISSN:
0929-5593
Viewed:
7542
Tracked:
3
Call For Papers
The primary goal of Autonomous Robots is to report on the theory and applications of robotic systems capable of some degree of self-sufficiency. Thus, the journal is aimed at the growing trend in robotics toward mobility, intelligence and autonomy in an unstructured world. This trend has been made possible by small, inexpensive, high-performance computers. The term `robot' implies that the systems described here are capable of performing purposeful behaviors in the real world. They obtain inputs from the world through sensors and act upon the world through actuators. The connection between sensing and actuation may be simple signal processing or it may involve complex decision making, goal interpretation and other aspects of reasoning. Most autonomous systems display some form of mobility: on land, under water, in the air or in space. The mobility may make use of wheels, legs, fins, rotors or other actuators. The focus is on the ability to move and be self-sufficient, not on whether the system is an imitation of biology. Of course, biological models for robotic systems are of major interest to the journal since living systems are prototypes for autonomous behavior.

Autonomous robots must be able to perform in the world. Hence, publication preference will be given to papers which include performance data on actual robots in the real world. Papers which include only simulation results will be considered for publication, but with a lower priority. Such papers should also include a section entitled `The path to implementation', where the transition from simulation to real world is discussed.

Papers published in these pages will report on original research in such areas as:

Control of autonomous robots
Real-time vision
Autonomous wheeled and tracked vehicles
Legged vehicles
Computational architectures for autonomous systems
Distributed architectures for learning, control and adaptation
Studies of autonomous robot systems
Sensor fusion
Theory of autonomous systems
Terrain mapping and recognition
Self-calibration and self-repair for robots
Self-reproducing intelligent structures
Genetic algorithms as models for robot development.
Last updated by Dou Sun in 2022-01-30
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