Obstacle Avoidance Control for Mobile Robots based on Vision

Nara, Shunsuke; Takahashi, Satoru

doi:10.1109/sice.2006.315455

Cited by 7 publications

(7 citation statements)

References 11 publications

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“…Prototypes of several smart wheelchairs have been developed, based on advanced technology. The navigation problem of mobile robots has been treated in Nara and Takahashi (2006), such that obstacles are avoided using vision information. In the method used, obstacles were detected (which were present in front of a mobile robot) by calculating the optical flow, after which the optimal trajectory for a robot was decided based on the area of detection.…”

Section: Related Workmentioning

confidence: 99%

Autonomous wheelchair under a predefined environment

Mathivanan¹,

Palani²

2019

Int. j. adv. appl. sci.

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This research work proposes a prototype of low-cost smart wheelchair design. The significance of this model of the wheelchair is to move autonomously around a known environment, following a definite path. Existing systems include control action using a joystick, voice recognition, head movements, and eye motion. However, these systems include limitations in terms of operating complexity, the environment in which it is used and cost. Most importantly, the limitation of the existing system is the need for the continuous effort of the user in controlling the wheelchair. Hence, this work targets to aid the physically challenged persons to have improved mobility without much of human effort. An automatic wheelchair model is proposed that empowers navigation without continuous steering of a wheelchair by the user in a known environment. The model includes a set of sensors, infrared, ultrasonic, RFID reader and tags. The other significant components are the compass module, ATmega microcontroller, and motors. This system was designed and developed to enable low cost, reduced time and effort of the user. This paper provides a comprehensive overview of the design and validation of the autonomous wheelchair system. Further, the sophistication towards the GPS enabled autonomous system could be extended, which works well in different new environments.

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Section: Related Workmentioning

confidence: 99%

Autonomous wheelchair under a predefined environment

Mathivanan¹,

Palani²

2019

Int. j. adv. appl. sci.

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“…This is defined like the distribution of apparent velocities of movement of brightness patterns in an image [2]. The optical flow is classified in the following ranges: a) intensity-based differential methods, b) multiconstraint methods, c) frequency-based methods, d) correlation-based methods, e) temporal refinement methods.…”

Section: Optical Flowmentioning

confidence: 99%

“…This algorithm allows the verification of the pixels on motion within the image. Therefore, this can be connected to describe the relative motion of the obstacle that can be characterized by the region that can collide with the mobile robot [2].…”

Section: Optical Flowmentioning

confidence: 99%

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Fuzzy control for obstacle avoiding in mobile robots using stereo vision algorithms

Gardeazabal

Ponomaryov

Chairez³

2011

2011 8th International Conference on Electrical Engineering, Computing Science and Automatic Control

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Stereo vision has been an active research field for several scientific communities. Most of the reported results have considered pure image treatment algorithms. Nevertheless, there are few methods that combine stereo vision with automatic control algorithms to regulate the position of mobile robots. In this paper, the combination of stereo vision image treatment algorithm with a type-1 fuzzy logic controller. This controller is designed to avoid the collision of the mobile robot with obstacles located within the space where a robot is moving. Indeed, the controller was designed to accomplish two tasks, the obstacle avoidance and the general movement in the region of activity for the mobile robot. The stereo vision algorithm was successfully implemented to calculate the distance between the mobile system and the obstacle (based on block-matching algorithms: exhaustive and pyramidal) as well as the attack angle between the same hurdle and the rotation performed by the robot (using the optical flow algorithm). The fuzzy controller was designed using simple rules based on the observed trajectories performed by the mobile robot within a model scenario used to test the controller performance. The complete system was implemented into a real mobile robot to prove the efficiency of the mixed scheme using stereo vision and fuzzy control subsystem. The resulted mobile system can avoid the obstacle in all experiments independently of the relative position between them.

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“…In which binocular stereo vision has outstanding advantage, it can restore the three-dimensional information of view through the images which were provided by the camera of right and left sides [5]. However, due to the parallax, matching the corresponding points which had been collected by a binocular stereo vision system were detected in both left and right images is difficult to solve.…”

Section: Introductionmentioning

confidence: 99%

Stereo Vision Robot Obstacle Detection Based on the SIFT

Shao

Liu

et al. 2010

2010 Second WRI Global Congress on Intelligent Systems

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This paper presents a method of binocular vision obstacle detection based on SIFT feature matching algorithm. First, a model of depth measurement based on stereo vision is built, it does not require resume the three-dimensional coordinate of spatial point under the world coordinate system. According to the characteristics of the model, we proposed the binocular stereo vision calibration method based on parallel optical axis; Finally, the pixel coordinates of matching points are extracted with SIFT feature matching algorithm and completed the distance detection of the obstacle. The experimental results demonstrated the feasibility and effectiveness of the method.

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Obstacle Avoidance Control for Mobile Robots based on Vision

Cited by 7 publications

References 11 publications

Autonomous wheelchair under a predefined environment

Autonomous wheelchair under a predefined environment

Fuzzy control for obstacle avoiding in mobile robots using stereo vision algorithms

Stereo Vision Robot Obstacle Detection Based on the SIFT

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