Integrated control architecture based on behavior and plan for mobile robot navigation

Robotica ◽  
1998 ◽  
Vol 16 (4) ◽  
pp. 387-399 ◽  
Author(s):  
Jiyoon Chung ◽  
Byeong-Soon Ryu ◽  
Hyun S. Yang

One of the most difficult challenges in mobile robotics is real-world navigation. A real world can change suddenly and this change makes the robot relinquish planning actions in advance. In order to overcome such a change, behavior-based navigation was introduced. However, it had a difficulty in planning deliberate actions and in communicating with humans.We propose a new control strategy combining both the merits of behavior-based and planner-based approaches. The architecture consists of three major parts: Behaviors, Planner, and Coordinator. The Planner plays two important roles: 1) as a flexible human interface and 2) as the planner itself. The Coordinator serves as an interface between Behaviors and Planner and guides Behaviors to accomplish meaningful tasks according to the guidelines from the Planner and the Position estimator.We also provide a brief description of the intelligent mobile robot CAIR-2 and for '95 IJCAI/AAAI Robot Competition and Exhibition when the robot was placed first in the Office Delivery event.

Author(s):  
Diego Gabriel Gomes Rosa ◽  
Carlos Luiz Machado de souza junior ◽  
Marco Antonio Meggiolaro ◽  
Luiz Fernando Martha

2003 ◽  
Vol 52 (4) ◽  
pp. 1335-1340 ◽  
Author(s):  
P. Rusu ◽  
E.M. Petriu ◽  
T.E. Whalen ◽  
A. Cornell ◽  
H.J.W. Spoelder

2016 ◽  
Vol 28 (4) ◽  
pp. 441-450 ◽  
Author(s):  
Naoki Akai ◽  
◽  
Yasunari Kakigi ◽  
Shogo Yoneyama ◽  
Koichi Ozaki ◽  
...  

[abstFig src='/00280004/02.jpg' width='300' text='Navigation under strong rainy condition' ] The Real World Robot Challenge (RWRC), a technical challenge for mobile outdoor robots, has robots automatically navigate a predetermined path over 1 km with the objective of detecting specific persons. RWRC 2015 was conducted in the rain and every robot could not complete the mission. This was because sensors on the robots detected raindrops and the robots then generated unexpected behavior, indicating the need to study the influence of rain on mobile navigation systems – a study clearly not yet sufficient. We begin by describing our robot’s waterproofing function, followed by investigating the influence of rain on the external sensors commonly used in mobile robot navigation and discuss how the robot navigates autonomous in the rain. We conducted navigation experiments in artificial and actual rainy environments and those results showed that the robot navigates stably in the rain.


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