1A1-H05 Autonomous Navigation of Hydraulically Actuated Hexapod Robot COMET-IV : The 2nd Report: Obstacle Avoidance with Laser Range Finder

2008 ◽  
Vol 2008 (0) ◽  
pp. _1A1-H05_1-_1A1-H05_4
Author(s):  
Kosuke FUTAGAMI ◽  
Yuji HARADA ◽  
Hiroshi OOROKU ◽  
Masaki OKU ◽  
Xiaowu LIN ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Navigation ◽  
Laser Range Finder ◽  
Range Finder ◽  
Hexapod Robot ◽  
Laser Range ◽  
Hydraulically Actuated

Study on Intelligent Obstacle Avoidance and Autonomous Navigation

2012 ◽  
Vol 182-183 ◽  
pp. 1333-1337
Author(s):  
Meng Long Cao ◽  
Li Na Sun
Keyword(s):  
Obstacle Avoidance ◽  
Autonomous Navigation ◽  
Fuzzy Reasoning ◽  
Sensor Data ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Unknown Environment

Precise navigation and localization of the autonomous rover in unknown environment is important both for its own safety as well as for its ability to accomplish engineering and scientific objectives. In order to navigation autonomously the rover should have the ability of apperceiving the environment and avoiding the obstacles. Laser range finder is used to rebuild the environment and fuzzy reasoning method is used to avoid obstacles. Most importantly the rover process the sensor data to produce an estimate of its position while concurrently building a map of the environment. The improved filter algorithm is proposed to make the method feasible.

scholarly journals Dynamic Track Management in MHT for Pedestrian Tracking Using Laser Range Finder

2015 ◽  
Vol 2015 ◽  
pp. 1-9
Author(s):  
Abdul Hadi Abd Rahman ◽  
Hairi Zamzuri ◽  
Saiful Amri Mazlan ◽  
Mohd Azizi Abdul Rahman ◽  
Yoshio Yamamoto ◽  
...  
Keyword(s):  
Real Time ◽  
Autonomous Navigation ◽  
Tracking System ◽  
Computational Cost ◽  
Laser Range Finder ◽  
Tracking Problem ◽  
Range Finder ◽  
Pedestrian Tracking ◽  
Laser Range ◽  
Track Management

Real time pedestrian tracking could be one of the important features for autonomous navigation. Laser Range Finder (LRF) produces accurate pedestrian data but a problem occurs when a pedestrian is represented by multiple clusters which affect the overall tracking process. Multiple Hypothesis Tracking (MHT) is a proven method to solve tracking problem but suffers a large computational cost. In this paper, a multilevel clustering of LRF data is proposed to improve the accuracy of a tracking system by adding another clustering level after the feature extraction process. A Dynamic Track Management (DTM) is introduced in MHT with multiple motion models to perform a track creation, association, and deletion. The experimental results from real time implementation prove that the proposed multiclustering is capable of producing a better performance with less computational complexity for a track management process. The proposed Dynamic Track Management is able to solve the tracking problem with lower computation time when dealing with occlusion, crossed track, and track deletion.

Using Laser Range Finder Obstacle Avoidance and Using TLD Positioning System of Mobile Robot

2015 ◽  
Vol 764-765 ◽  
pp. 730-734
Author(s):  
Jr Hung Guo ◽  
Kuo Lan Su
Keyword(s):  
Obstacle Avoidance ◽  
Imaging System ◽  
Recognition System ◽  
Laser Range Finder ◽  
Range Finder ◽  
Detection Range ◽  
Laser Range ◽  
Sensing System ◽  
Reflection Data ◽  
Reflectance Data

Robot self-localization and obstacle avoidance has been one of the important topics in robotics. The sensing system which is more mature and using a laser range finder (LRF). But the biggest drawback is the LRF detection range is a plane, And for some high reflectivity of the object, will produce incorrect reflection data. So when the obstacle is not the detection range, or due to high reflectance data will generate an error and the positioning of the robot obstacle avoidance function error. This paper is the use of TLD (Tracking-Learning-Detection) image recognition system, to assist LRF do positioning and obstacle avoidance. And this imaging system can also be used while the robot with object tracking functions

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