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A Practical Path Planner for the Robotic Vacuum Cleaner in Rectilinear Environments
Nakju Lett Doh,Chanki Kim,Wan Kyun Chung IEEE 2007 IEEE transactions on consumer electronics Vol.53 No.2
<P>In this paper, we propose a path planner for a robotic vacuum cleaner (RVC). In the design of the planner, we consider two main issues: (1) human-friendly path generation and (2) low computational load. First, we analyze how human move and suggest a hypothesis that human navigate in a way that minimizes the sum of muscle and brain energy. By imitating the human path, we propose a human- friendly path planner. Also, the designed planner requires a low amount of computations which not only extends the battery running time but also decreases the hardware cost of the RVC. Experimental results show that the proposed path gives a more favorable impression to customers than conventional paths.</P>
A robust localization algorithm in topological maps with dynamic noises
Lee, Kyungmin,Doh, Nakju Lett,Chung, Wan Kyun,Lee, Seoung Kyou,Nam, Sang-Yep Emerald Group Publishing Limited 2008 The Industrial robot Vol.35 No.5
<B>Purpose</B> - The paper's purpose is to propose a localization algorithm for topological maps constituted by nodes and edges in a graph form. The focus is to develop a robust localization algorithm that works well even under various dynamic noises. <B>Design/methodology/approach</B> - For robust localization, the authors propose an algorithm which utilizes all available data such as node information, sensor measurements at the current time step (which are used in previous algorithms) and edge information, and sensor measurements at previous time steps (which have not been considered in other papers). Also, the algorithm estimates a robot's location in a multi-modal manner which increases its robustness. <B>Findings</B> - Findings show that the proposed algorithm works well in topological maps with various dynamics which are induced by the moving objects in the map and measurement noises from cheap sensors. <B>Originality/value</B> - Unlike previous approaches, the proposed algorithm has three key features: usage of edge data, inclusion of history information, and a multi-modal based approach. By virtue of these features, the paper develops an algorithm that enables robust localization performance.
Full-DOF Calibration of a Rotating 2-D LIDAR With a Simple Plane Measurement
Kang, Jaehyeon,Doh, Nakju Lett IEEE 2016 IEEE transactions on robotics Vol.32 No.5
<P>This paper proposes a calibration method that accurately estimates six parameters between the two centers of 2-D light detection and ranging (LIDAR) and a rotating platform. This method uses a simple plane, and to the best of our knowledge, it is the first to enable full-degree-of-freedom (DOF) estimation without additional hardware. The key concept behind this method is a decoupling property, in which the direction of a line on a plane does not contain 3-DOF translation terms. Based on this, a cost function for rotation is constructed, and 3-DOF rotation parameters are estimated. With this rotation, the remaining 3-DOF translation parameters are calculated in a manner that minimizes the cost function for translation only. In other words, an original 6-DOF problem is decoupled into two 3-DOF estimation problems. Given these cost functions, degenerate cases are mathematically analyzed for known cases (incomplete), and the robustness is numerically tested for all possible cases (complete). The performance of themethod is validated by extensive simulations and experimentations, and the estimated parameters from the proposed method demonstrate better accuracy than previous methods.</P>
Automatic CAD-structure extraction from 3D point clouds
Jihyeon Kwon,Nakju Lett Doh 한국정보통신학회 2015 2016 INTERNATIONAL CONFERENCE Vol.7 No.1
When we cannot use an original blueprint due to undocumented interior renovation or loss, we have measured and drawn structures manually. However, it is too time-consuming and inconvenient. Moreover, many objects placed in a room often occlude corners and edges of the room, which makes 3D indoor structure modeling more difficult. In this paper, we propose a new method for 3D indoor structure reconstruction which results in a simple CAD-structure with automatic process. For data collection of the indoor environment, we used a 3D laser sensor. For modeling structures, we classify the obtained 3D point clouds as structures and objects. Plane extraction among structure-PCD is followed since an extracted plane is intuitively part of a wall considering that indoor space is enclosed with walls. From the extracted planes, we seek points where three planes intersect since some intersection points are occluded by objects placed at the corner. Then several valid intersection points are determined as real structure points by the Plane-Patch test, eliminating other points that do not really exist. After that, we connect the valid structurepoints belonging to the ceiling, which creates a contour. With this, we can generate a floor plan of an indoor room. Considering the distance between the ceiling and the floor, finally, we reconstruct the 3D indoor structure as a simple CAD model. We applied this method to an indoor environment which consists of four rooms and obtained the results successfully.
Observability Analysis of 2D Geometric Features using the Condition Number for SLAM Applications
Suyong Yeon,Nakju Lett Doh 제어로봇시스템학회 2013 제어로봇시스템학회 국제학술대회 논문집 Vol.2013 No.10
Observability analysis is a very powerful tool for discriminating whether a robot can estimate its own state. However, this method cannot investigate how much of the system is observable. This is a major problem from a state estimation perspective because there is too much noise in real environments. Therefore, although the system (or a mobile robot) is observable, it cannot estimate its own state. To address this problem, we propose an observability analysis method that uses the condition number. Mathematically, the condition number of matrix represents a degree of robustness to noise. We utilize this property of the condition number to investigate the degree of observability. In other words, the condition number of the observability matrix demonstrates the feasibility of state estimation and the robustness of its feasibility for estimation.