Behavior-based autonomous cooperative control of intelligent mobile robot systems with embedded Petri nets

This paper is concerned with Q-learning , a very popular algorithm for reinforcement learning ,for obstacle avoidance through neural networks. The principle tells that the focus always must be on both ecological nice tasks and behaviours when designing on robot. Many robot systems have used behavior-based systems since the 1980’s.In this paper, the Khepera robot is trained through the proposed algorithm of Q-learning using the neural networks for the task of obstacle avoidance. In experiments with real and simulated robots, the neural networks approach can be used to make it possible for Q-learning to handle changes in the environment.

Download Full-text

A Bio-Inspired, Distributed Control Approach to the Design of Autonomous Cooperative Behaviors in Multiple Mobile Robot Systems

Advanced Methodologies and Technologies in Artificial Intelligence, Computer Simulation, and Human-Computer Interaction - Advances in Computer and Electrical Engineering ◽

10.4018/978-1-5225-7368-5.ch077 ◽

2019 ◽

pp. 1058-1070

Author(s):

Gen'ichi Yasuda

Keyword(s):

Mobile Robot ◽

Distributed Control ◽

Cooperative Control ◽

Behavioral Control ◽

Discrete Event ◽

Control Approach ◽

Robot Systems ◽

Command Input ◽

High Level ◽

Control Modules

This chapter deals with the design and implementation of bio-inspired control architectures for intelligent multiple mobile robot systems. Focusing on building control systems, this chapter presents a non-centralized, behavior-based methodology for autonomous cooperative control, inspired by the adaptive and self-organizing capabilities of biological systems, which can generate robust and complex behaviors through limited local interactions. With autonomous behavior modules for discrete event distributed control, a modular, Petri net-based behavioral control software has been implemented in accordance with a hierarchical distributed hardware structure. The behavior modules with respective pre-conditions and post-conditions can be dynamically connected in response to status events from action control modules at the lower level to achieve the specified overall task. The approach involving planning, control, and reactivity can integrate high-level command input with the behavior modules through the distributed autonomous control architecture.

Download Full-text

A Bio-Inspired, Distributed Control Approach to the Design of Autonomous Cooperative Behaviors in Multiple Mobile Robot Systems

Encyclopedia of Information Science and Technology, Fourth Edition ◽

10.4018/978-1-5225-2255-3.ch592 ◽

2018 ◽

pp. 6836-6846

Author(s):

Gen'ichi Yasuda

Keyword(s):

Mobile Robot ◽

Distributed Control ◽

Cooperative Control ◽

Behavioral Control ◽

Discrete Event ◽

Control Approach ◽

Robot Systems ◽

Command Input ◽

High Level ◽

Control Modules

This chapter deals with the design and implementation of bio-inspired control architectures for intelligent multiple mobile robot systems. Focusing on building control systems, this chapter presents a non-centralized, behavior-based methodology for autonomous cooperative control, inspired by the adaptive and self-organizing capabilities of biological systems, which can generate robust and complex behaviors through limited local interactions. With autonomous behavior modules for discrete event distributed control, a modular, Petri net based behavioral control software has been implemented in accordance with a hierarchical distributed hardware structure. The behavior modules with respective pre-conditions and post-conditions can be dynamically connected in response to status events from action control modules at the lower level to achieve the specified overall task. The approach involving planning, control and reactivity can integrate high-level command input with the behavior modules through the distributed autonomous control architecture.

Download Full-text