Putra Pandu Adikara

A laser-vision based obstacle detection and distance estimation for smart wheelchair navigation

The aim of the research is to present an approach of obstacle distance estimation and navigation for smart wheelchair. The smart wheelchair is an electric wheelchair equipped with camera and line laser to navigate and avoid an obstacle. The camera was used to capture images from the environment to sense the pathway condition. The line laser was used in combination with camera to recognize an obstacle in the pathway based on the shape of line laser image in certain angle. A blob method detection was applied on the line laser image to recognize the pattern of the detected obstacles. The line laser projector and camera were mounted in fixed-certain position to make sure a fixed relation between blobs-gaps and obstacle-to-wheelchair distance. A simple linear regression from 16 obtained data was used to represent this relation as the estimated obstacle distance. As a result, the average error between the estimation and actual distance was 1.25 cm from 7 data testing experiments. The experiments result indicates that the proposed method is able to estimate well the distance between wheelchair and obstacle. Later, the smart wheelchair needs to decide further action whether it should turn left, right or just walk straight when facing certain obstacle to avoid it.

Adaptive human tracking for smart wheelchair

People with impairment and having difficulties to walk, even impossible to move due to illness, injury, or disability need assistance tool. One assistance tool to help those people is wheelchair. With current technological developments, conventional wheelchair can be improved. Conventional wheelchair which operated by hand cannot be used by people with hand-foot impairment, as well as electric-powered wheelchair that need to be controlled with hand. For those with hand-foot impairment, conventional wheelchair can be assisted by assistant to help pushing and to maneuver. One drawback with this approach is the assistant will have limited movement and will have fatigue from pushing a wheelchair. This research try to overcome this drawback so that the wheelchair can move semi-autonomously. Proposed approach incorporates human tracking algorithm that later will be used to make the wheelchair moving independently without assistant to push from behind. This paper propose a framework that combines keypoint descriptors for human tracking: ORB, KAZE, AKAZE, BRISK, SIFT, and SURF. Each keypoint descriptors are given a score which is used to choose which descriptor is used until the minimum number of keypoints is fulfilled. If the best in the method list does not suffice, then the second best will be selected to generate keypoints, and so on. The result of the framework obtained high precision, 0.93 and 0.89 from two videos with different environments.

Onward movement detection and distance estimation of object using disparity map on stereo vision

The object tracking is used as instruction controller in wheelchair that track the movement direction of object along time. The movement direction include left, right and onward. The left and right direction can be calculated by using the changing of x-coordinate of object in every sub sequence frame. The challenge is to determine the onward moving. The onward moving cannot calculate simply by coordinate of object in 2D. The solution to detect the onward moving is by using the stereo vision camera. We proposed a method to detect the onward movement and calculate the distance of object from camera using stereo vision. The detection rate is 83.1%. The estimation of object distance from the camera is actually only 3–4 meters away. The system detect that the distance of object is 0–5 meters in front of the camera. The determination of distance estimation is appropriate with the actual distance state.

Development of computer vision based obstacle detection and human tracking on smart wheelchair for disabled patient

People with physical disability such as quadriplegics may need a device which assist their mobility. Smart wheelchair is developed based on conventional wheelchair and is also generally equipped with sensors, cameras and computer based system as main processing unit to be able to perform specific algorithm for the intelligent capabilities. We develop smart wheelchair system that facilitates obstacle detection and human tracking based on computer vision. The experiment result of obstacle distance estimation using RANSAC showed lower average error, which is only 1.076 cm compared to linear regression which is 2.508 cm. The average accuracy of human guide detecting algorithm also showed acceptable result, which yield over 80% of accuracy.

Optimizing K-means text document clustering using latent semantic indexing and pillar algorithm

Document clustering is an important tool to help managing the vast amount of digital text document. This paper introduces a new approach to cluster text document. First, text is preprocessed and indexed using inverted index. Then the index is trimmed using TF-DF thresholding. After that, Term Document Matrix is built based on TF-IDF. Next step uses Latent Semantic Indexing to extract important feature from Term Document Matrix. The following process is selecting seeds via Pillar algorithm. Based on determined seeds, K-Means clustering is performed. Experiment result proves that this approach outperforms standard K-Means document clustering.