We propose a new camera-lidar fusion method for road detection where the spherical coordinate transformation is introduced to decrease the gap between the point cloud of 3D lidar data. The camera's color data and the 3D lidar's height data are transformed into the same spherical coordinate, and then input to the convolution neural network for segmentation. Faster segmentation is possible due to the reduced size of input data. To increase the detection accuracy, this modified SegNet expands the receptive field of the network. Using the KITTI dataset, we present the experimental results to show the usefulness of the proposed method.

The problem with lidar placement is finding a lidar position that reduces the dead zone and improves the point cloud resolution. A lidar placement method is thus proposed for the multiple lidar system of autonomous vehicles to resolve this problem. With the introduction of the lidar occupancy grid, the problem is formulated as an optimization problem. A genetic algorithm is subsequently applied to solve the optimization problem. The experimental results using commercial lidars are subsequently presented to show the usefulness of the proposed method.

A fast lidar-camera fusion method is proposed to detect road in autonomous vehicles. The height data of lidar is transformed to spherical coordinate system to increase the data density. The RGB data of camera is also transformed to spherical coordinate system to match with the lidar data. The amount of data is greatly reduced by spherical coordinate transformation, which results in the fast running time. The transformed images of height, red, green, and blue are input to the CNN. A dilated convolution structure is newly proposed to improve the learning accuracy by expanding the receptive field of CNN. The experimental results using the KITTI data set are finally presented to show the usefulness of the proposed method.

An effective method to segment vehicles and roads is proposed for autonomous vehicles using low-channel 3D lidar. The distance-view transformation is newly proposed to overcome the low density of top-view data of lidar. In addition, a dilated convolution structure is proposed to expand the receptive field of a convolutional neural network. The proposed network improves the accuracy of segmentation. The experimental results are presented to verify the usefulness of the proposed method.

We propose an optimization method to maximize the productivity of PCB (printed circuit board) assembly of modular mounters. The modular mounter is a series of compact SMD (surface mount device) placement modules, where each module has assembly head and feeder lanes. The throughput of the mounter is maximized by balancing the assembly time of each module. We indentify the problem as an integer programming problem, and divide the problem into feeder arrangement problem and mount sequence problem by decoupling the path into forward arcs and backward arcs. The integer-programming based algorithms such as branch-and-bound algorithm and transportation algorithm are applied to solve the formulated problems. Simulation results are presented to verify the usefulness of the proposed method.

We propose an image segmentation method for automatic paper-money inspection system. The UV (ultra violet) patterns embedded in the paper money should be segmented to determine whether the money is genuine or not. We acquired the image by directional lighting system using UV LEDs. In order to segment the pattern from the background, we apply the Gaussian mixture model to consider the multi-modal characteristics of the histogram. Experimental results are presented to verify the performance of the proposed method.

This paper considers the problem of minimizing the assembly time of multi-head surface mounting machines. The problem is decomposed into a hierarchy of related subproblems. Since all subproblems in the hierarchy are known to be of a combinatorial nature and computationally intractable, we develop heuristics which are based on dynamic programming and the nearest neighbour travelling salesman problem technique. We implement the method as a computer program and perform computer simulations. The results are compared to a heuristic that is currently in use.

The concept of dynamic tracking line is proposed as the feasible tracking region for a robot in a robot-conveyor system, which takes the conveyor speed into consideration. This paper presents an effective method to find the dynamic tracking line in a robotic workcell. The maximum permissible line-speed which is a quantitative measure of the robot capability for conveyor tracking, is defined on the basis of the relation between the end-effector speed and the bounds on the joint velocities, accelerations, and torques. This measure is derived in an analytic form using the parameterized dynamics and kinematics of the manipulator, and some of its properties are established mathematically. The problem of finding the dynamic tracking line is then formulated as a root-solving problem for a single-variable equation, and solved by the use of a simple numerical technique. Finally, numerical examples are presented to demonstrate the methodology and its applications in workspace specification.

The concept of dynamic tracking line is proposed as the feasible tracking region for a robot in a robot-conveyor system, which takes the conveyor speed into consideration. This paper presents an effective method to find the dynamic tracking line in a robotic workcell. The maximum permissible line-speed which is a quantitative measure of the robot capability for conveyor tracking, is defined on the basis of the relation between the end effector speed and the bounds on the joint velocities, accelerations, and torques. This measure is derived in an analytic form using the parameterized dynamics and kinematics of the manipulator, and some of its properties are established mathematically. The problem of finding the dynamic tracking line is then formulated as a root-solving problem for a single-variable equation, and solved by the use of a simple numerical technique. Finally, numerical examples are presented to demonstrate the methodology and its applications in workspace specification.

The concept of dynamic tracking line is proposed as the feasible tracking region for a robot in a robot-conveyor system, which takes the variable conveyor speed into consideration. This paper presents an effective method to find the dynamic tracking line in a robotic workcell. The maximum permissible line-speed which is a quantitative measure of the robot capability for conveyor tracking, is defined on the basis of the relation between the end-effector speed and the bounds on the joint velocities, accelerations, and torques. This measure is derived in an analytic form, and some of its properties are established mathematically. The problem of finding the dynamic tracking line is then formulated as a root-solving problem for a single-variable equation, and solved by the use of a simple numerical technique.

The robot motion is analyzed and planned for conveyor tracking considering the speed of the conveyor belt and the location of the part and the robot. The joint torque limit, together with the joint velocity, acceleration, and jerk limits of the robot, is also taken into account in the motion analysis and planning. To include the robot arm dynamics, the problem is formulated as second-order state equations using a parametric function. The conveyor tracking problem is then converted to an optimal tracking problem. The solution that minimizes the specified performance index is obtained using the dynamic programming approach. Numerical examples are finally presented to demonstrate the significance of the proposed method for conveyor tracking of the robot in a workcell.>

Robot motion is analyzed and planned for conveyor tracking considering the speed of the conveyor belt and the locations of the part and the robot. The joint torque limit, joint velocity, acceleration, and jerk limits of the robot are taken into account in the motion analysis and planning. To include the robot arm dynamics, the problem is formulated as second order state equations using a parametric function. The conveyor tracking problem is then converted to an optimal tracking problem. The solution that minimizes the specified performance index is obtained using the dynamic programming approach. Numerical examples are presented to demonstrate the significance of the proposed method for conveyor tracking of the robot in a workcell.>