Explicitly Task Oriented Probabilistic Active Vision for a Mobile Robot

2009 ◽  
pp. 85-96 ◽  
Author(s):  
Pablo Guerrero ◽  
Javier Ruiz-del-Solar ◽  
Miguel Romero
Keyword(s):  
Mobile Robot ◽  
Active Vision ◽  
Task Oriented

scholarly journals Multi-Focal Vision and Gaze Control Improve Navigation Performance

10.5772/50920 ◽  
2012 ◽  
Vol 9 (1) ◽  
pp. 25 ◽  
Author(s):  
Kolja Kühnlenz ◽  
Martin Buss
Keyword(s):  
Mobile Robot ◽  
Robot Navigation ◽  
Active Vision ◽  
Path Following ◽  
Mobile Robot Navigation ◽  
Vision Systems ◽  
Localization Accuracy ◽  
Localization And Mapping ◽  
Novel Concept ◽  
The Impact

Multi-focal vision systems comprise cameras with various fields of view and measurement accuracies. This article presents a multi-focal approach to localization and mapping of mobile robots with active vision. An implementation of the novel concept is done considering a humanoid robot navigation scenario where the robot is visually guided through a structured environment with several landmarks. Various embodiments of multi-focal vision systems are investigated and the impact on navigation performance is evaluated in comparison to a conventional mono-focal stereo set-up. The comparative studies clearly show the benefits of multi-focal vision for mobile robot navigation: flexibility to assign the different available sensors optimally in each situation, enhancement of the visible field, higher localization accuracy, and, thus, better task performance, i.e. path following behavior of the mobile robot. It is shown that multi-focal vision may strongly improve navigation performance.

Path planning of a mobile robot using genetic heuristics

Robotica ◽  
1998 ◽  
Vol 16 (5) ◽  
pp. 575-588 ◽  
Author(s):  
Andreas C. Nearchou
Keyword(s):  
Genetic Algorithm ◽  
Path Planning ◽  
Mobile Robot ◽  
Optimal Path ◽  
Hill Climbing ◽  
Planning Problem ◽  
Well Performance ◽  
Simulation Results ◽  
Task Oriented ◽  
Path Planning Problem

A genetic algorithm for the path planning problem of a mobile robot which is moving and picking up loads on its way is presented. Assuming a findpath problem in a graph, the proposed algorithm determines a near-optimal path solution using a bit-string encoding of selected graph vertices. Several simulation results of specific task-oriented variants of the basic path planning problem using the proposed genetic algorithm are provided. The results obtained are compared with ones yielded by hill-climbing and simulated annealing techniques, showing a higher or at least equally well performance for the genetic algorithm.

Realizing active vision by a mobile robot

2002 ◽  
Author(s):  
S. Li ◽  
I. Miyawaki ◽  
H. Ishiguro ◽  
S. Tsuji
Keyword(s):  
Mobile Robot ◽  
Active Vision

Behavior-Based Fuzzy Control of Obstacle Avoidance for Indoor Mobile Robot

2010 ◽  
Vol 34-35 ◽  
pp. 482-486
Author(s):  
De Hai Chen ◽  
Yu Ming Liang
Keyword(s):  
Mobile Robot ◽  
Obstacle Avoidance ◽  
Fuzzy Controller ◽  
Input Parameter ◽  
Middle Level ◽  
Infrared Range ◽  
Indoor Mobile Robot ◽  
Behavior Based ◽  
Task Oriented ◽  
And Task

This paper describes indoor mobile robot covering path to avoid obstacle based on behavior fuzzy controller. The robot measures the distance to obstacle with ultrasonic sensors and infrared range sensors, and the distance is the input parameter of the behavior-based fuzzy controller. The behavior architecture has three levels behaviors: emergency behavior, obstacle avoidance behavior, and task oriented behavior. The task oriented behavior is the highest level behavior, and has two subtasks: wall following and path covering. The middle level behavior is obstacle avoidance. The lowest level is an emergency behavior, which is the highest priority behavior. The simulation result demonstrates that each behavior works correctly.

REALIZING FACE-TO-FACE INTERACTION BY VIEW-BASED TRACKING

2002 ◽  
Vol 01 (02) ◽  
pp. 331-347 ◽  
Author(s):  
SHIGANG LI ◽  
FUJI REN
Keyword(s):  
Mobile Robot ◽  
Visual Feedback ◽  
Skin Color ◽  
Active Vision ◽  
Real Image ◽  
Color Distribution ◽  
Face To Face ◽  
The Face ◽  
Facial Pattern

In this paper, we propose a method of realizing face-to-face interaction by view-based tracking between a human and a mobile robot. Although individuals can be recognized easily by observing frontal faces, it is difficult to do it from profiles of face. To cope with this problem, our mobile robot first finds face-like areas based upon the skin color distribution which is made from real image samples. Second, a facial pattern in the image is found and its direction relative to the robot is estimated in terms of the memorized views. Finally, the mobile robot moves to the front of the face according to the face direction while tracking the face by using visual feedback based upon active vision approach.

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