• International Journal of Control, Automation, and Systems
• /
• v.3 no.1
• /
• pp.1-14
• /
• 2005

This paper presents an obstacle detection algorithm based on the consecutive and the cooperative range sensor scanning schemes. For a known environment, a mobile robot scans the surroundings using a range sensor that can rotate 3600°. The environment is rebuilt using nodes of two adjacent walls. The robot configuration is then estimated and an obstacle is detected by comparing characteristic points of the sensor readings. In order to extract edges from noisy and inaccurate sensor readings, a filtering algorithm is developed. For multiple robot localization, a cooperative scanning method with sensor range limit is developed. Both are verified with simulation and experiments.

• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.3101-3104
• /
• 1999

It is important to detect objects movement for obstacle recognition and path searching of autonomous robots and vehicles with vision sensor. This paper shows the method to draw out objects and to trace the trajectory of the moving object using a CCD camera and it describes the method to recognize the shape of objects.

• Proceedings of the KIEE Conference
• /
• 1996.07b
• /
• pp.1251-1253
• /
• 1996

The vision processing system for mobile robots requires real time processing and reliability for the purpose of safe navigation. But, general types of vision systems are not appropriate owing to the correspondence problem which correlates the points out of two images. To determine the obstacle area, we use correspondences of line segments between two perspective images sequentially acquired by camera. To simplify the correspondence, the matching of line segments are performed in the navigation space, based on the assumption that mobile robot should be navigated in the flat surface and the motion of mobile robot between two frames should be approximately known.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.56 no.2
• /
• pp.407-414
• /
• 2007

A sensor fault detection scheme(SFDS) for a class of nonlinear systems that can be represented by Takagi-Sugeno fuzzy model is proposed. Basically, the SFDS may be considered as a multiple observer scheme(MOS) in which the bank of state observers and the detection & isolation logic are included. However, the proposed scheme has two great differences from the conventional MOSs. First, the proposed scheme includes fuzzy fault detection observers(FFDO) that are constructed based on the T-S fuzzy model that provides very good approximation to nonlinear dynamic systems. Secondly, unlike the conventional MOS, the FFDOS are driven not parallelly but sequentially according to the predetermined sequence to avoid the massive computational burden, which is known to be the biggest obstacle to the practical application of the multiple observer based FDI schemes. During the operating time, each FFDO generates the residuals carrying the information of a specified fault, and the corresponding fault detection logic unit performs the logical operations to detect and isolate the fault of interest. The proposed scheme is applied to an inverted pendulum control system for sensor fault detection/isolation. Simulation study shows the practical feasibility of the proposed scheme.

• Journal of Institute of Control, Robotics and Systems
• /
• v.20 no.8
• /
• pp.868-874
• /
• 2014

This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

• Journal of the Society of Naval Architects of Korea
• /
• v.38 no.4
• /
• pp.23-29
• /
• 2001

An Obstacle Avoidance System(OAS) of Underwater Vehicle(UV) in diving and steering plane is investigated. The concept of Imaginary Reference Line(IRL), which acts as the seabed in the diving plane, is introduced to apply the diving plane avoidance algorithm to the steering plane algorithm. Furthermore, the distance to the obstacle and the slope information of the obstacle are used for more efficient and safer avoidance. As for the control algorithm, the sliding mode controller is adopted to consider the nonlinearity of the equations of motion and to get the robustness of the designed system. To verify the obstacle avoidance ability of the designed system, numerical simulations are carried out on the cases of some presumed three-dimensional obstacles. The effects of the sonar and the clearance factor used in avoidance algorithm are also investigated. Through these, it is found that the designed avoidance system can successfully cope with various obstacles and the detection range of sonar is proven to bea significant parameter to the performance of the avoidance.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.6 no.1
• /
• pp.115-123
• /
• 2002

In this paper, we present two types of vision algorithm that mobile robot has CCD camera. for obstacle avoidance and path plan. One is simple algorithm that compare with grey level from input images. Also, The mobile robot depend on image processing and move command from PC host. we has been studied self controlled mobile robot system with CCD camera. This system consists of TMS320F240 digital signal processor, step motor, RF module and CCD camera. we used wireless RF module for movable command transmitting between robot and host PC. This robot go straight until 95 percent filled screen from input image. And the robot recognizes obstacle about 95 percent filled something, so it could avoid the obstacle and conclude new path plan. Another is complex algorithm that image preprocessing by edge detection, converting, thresholding and image processing by labeling, segmentation, pixel density calculation.

• The Journal of the Korea Contents Association
• /
• v.19 no.3
• /
• pp.72-79
• /
• 2019

Autonomous locomotion has two essential functionalities: mapping builds and updates maps by uncertain position information and measured sensor inputs, and localization is to find the positional information with the inaccurate map and the sensor information. In addition, obstacle detection, avoidance, and path designs are necessarily required for autonomous locomotion by combining the probabilistic methods based on uncertain locations. The sensory inputs, which are measured by a metric-based scanner, have difficulties of distinguishing moving obstacles like humans from static objects like walls in given environments. This paper proposes the low resolution grid map combined with reinforcement learning, which is compared with the conventional recognition method for detecting static and moving objects to generate obstacle avoiding path. Finally, the proposed method is verified with experimental results.

• Journal of KIISE:Software and Applications
• /
• v.36 no.4
• /
• pp.291-297
• /
• 2009

This paper introduces an electronic travel aid, named SmartWand, which detects obstacles using a ultrasonic sensor. In addition to obstacle detection, the SmartWand senses color information of objects and the environmental brightness. It is designed to be attached to a ordinary white cane in order to detect the obstacles at head-hight which cannot be covered by the cane. We have improved the first version of the SmartWand based on a user evaluation. The second version is much lighter and smaller than the previous one. It has been enhanced by two new functions. The SmartWand eliminates impact errors due to tapping the ground using a moving average filtering algorithm and restricts the detection range to the path in the moving direction using an acceleration sensor. We have tested these functions in various environments to determine the parameters for these functions.

• 제어로봇시스템학회:학술대회논문집
• /
• 2004.08a
• /
• pp.1416-1418
• /
• 2004

This paper proposes an image processing algorithm for detecting obstacles on road-lane using DLI(disparity of lane-related information) that is generated by stereo images acquired from dual cameras mounted on a moving vehicle. The DLI is a disparity that is acquired using single lane information from road lane detection. For the purpose to reduce processing time, we use small blocks obtained by edge-histogram based blocking logic. This algorithm detects moving objects such as preceding vehicles and obstacles. The proposed algorithm has been implemented in a personal computer with the road image data of a typical highway. We successfully performed experiments under a wide variety of road conditions without changing parameter values or adding human intervention. Experimental results also showed that the proposed DLI is quite successful.