Limits...
Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

Yi DH, Lee TJ, Cho DI - Sensors (Basel) (2015)

Bottom Line: We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system.Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m.The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, Automation and Systems Research Institute (ASRI), Seoul National University, Seoul 151-742, Korea. ydh01@snu.ac.kr.

ABSTRACT
This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

No MeSH data available.


Floor materials used in this work: (a) texture-style carpet; (b) loop-style carpet; (c) laminate floor; and (d) vinyl sheet.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4481980&req=5

sensors-15-11208-f006: Floor materials used in this work: (a) texture-style carpet; (b) loop-style carpet; (c) laminate floor; and (d) vinyl sheet.

Mentions: Most of the causes of height variation in indoor navigation, excluding variations associated with robot suspension, are rough carpet, doorsills, low obstacles, uneven ground, and any objects that a robot can climb. To verify the feasibility of the fabricated afocal OFS module in these environments, four types of floor materials were selected for experiments: laminated floor; vinyl sheet; texture-style carpet; and loop-style carpet (Figure 6). The height between the OFS and the surface of the material is varied from 30 to 50 mm in seven steps, and the sensor module is moved by the robotic gantry system over a distance of 80 cm at a speed of 35 cm/s. The same experiments are repeated 10 times, and the image quality is examined every 5 mm in the experimental height interval.


Afocal optical flow sensor for reducing vertical height sensitivity in indoor robot localization and navigation.

Yi DH, Lee TJ, Cho DI - Sensors (Basel) (2015)

Floor materials used in this work: (a) texture-style carpet; (b) loop-style carpet; (c) laminate floor; and (d) vinyl sheet.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4481980&req=5

sensors-15-11208-f006: Floor materials used in this work: (a) texture-style carpet; (b) loop-style carpet; (c) laminate floor; and (d) vinyl sheet.
Mentions: Most of the causes of height variation in indoor navigation, excluding variations associated with robot suspension, are rough carpet, doorsills, low obstacles, uneven ground, and any objects that a robot can climb. To verify the feasibility of the fabricated afocal OFS module in these environments, four types of floor materials were selected for experiments: laminated floor; vinyl sheet; texture-style carpet; and loop-style carpet (Figure 6). The height between the OFS and the surface of the material is varied from 30 to 50 mm in seven steps, and the sensor module is moved by the robotic gantry system over a distance of 80 cm at a speed of 35 cm/s. The same experiments are repeated 10 times, and the image quality is examined every 5 mm in the experimental height interval.

Bottom Line: We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system.Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m.The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, Automation and Systems Research Institute (ASRI), Seoul National University, Seoul 151-742, Korea. ydh01@snu.ac.kr.

ABSTRACT
This paper introduces a novel afocal optical flow sensor (OFS) system for odometry estimation in indoor robotic navigation. The OFS used in computer optical mouse has been adopted for mobile robots because it is not affected by wheel slippage. Vertical height variance is thought to be a dominant factor in systematic error when estimating moving distances in mobile robots driving on uneven surfaces. We propose an approach to mitigate this error by using an afocal (infinite effective focal length) system. We conducted experiments in a linear guide on carpet and three other materials with varying sensor heights from 30 to 50 mm and a moving distance of 80 cm. The same experiments were repeated 10 times. For the proposed afocal OFS module, a 1 mm change in sensor height induces a 0.1% systematic error; for comparison, the error for a conventional fixed-focal-length OFS module is 14.7%. Finally, the proposed afocal OFS module was installed on a mobile robot and tested 10 times on a carpet for distances of 1 m. The average distance estimation error and standard deviation are 0.02% and 17.6%, respectively, whereas those for a conventional OFS module are 4.09% and 25.7%, respectively.

No MeSH data available.