• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.5
• /
• pp.397-404
• /
• 2011

This paper proposes an algorithm capable of extracting corresponding points between a pair of stereo images based on dynamic programming. The purpose of extracting the corresponding points is to provide the stereo disparity data to a road-slope estimation algorithm with high accuracy and in real-time. As the road-slope estimation algorithm does not require dense disparity data, the proposed stereo matching algorithm aims at extracting corresponding points accurately and quickly. In order to realize this contradictory goal, this paper exploits dynamic programming, and minimizes matching candidates using vertical components of color edges. Furthermore, the typical occlusion problem in stereo vision is solved. The proposed algorithm is proven to be effective through experiments with various images captured on the roads.

• Journal of Institute of Control, Robotics and Systems
• /
• v.22 no.12
• /
• pp.1040-1045
• /
• 2016

An inventory control system was developed for multiproduct batch plants with an arbitrary number of batch processes and storage units. Customer orders are received by the plant at intervals and in quantities that are subject to random fluctuations. The objective of the plant operation is to minimize the total cost while maintaining inventory levels within the storage or warehouse capacity by adjusting the startup times, the quantities of raw material orders, and production batch sizes. An adaptive model-based control algorithm was developed that uses a periodic square wave model to represent the flows of material between the processes and the storage units. The effectiveness of this approach was demonstrated by performing simulations.

• The Journal of Korea Robotics Society
• /
• v.1 no.1
• /
• pp.46-57
• /
• 2006

It is well known that mathematical solutions for multi-agent planning problems are very difficult to obtain due to the complexity of mutual interactions among multi-agent. Most of the past research results thus are based on the probabilistic completeness. However, the practicality and effectiveness of the solution from the probabilistic completeness is significantly reduced by heavy computational burden. In this paper, we propose a practically applicable solution technique for multi-agent planning problems, which assures a reasonable computation time and a real world application for more than 3 multi-agents for the case of general shaped paths in agent movement. First, to reduce the computation time, a collision map is utilized for detecting potential collisions and obtaining collision-free solutions for multi-agents. Second, to minimize the maximum of multi-agent task execution time, a method is developed for selecting an optimal priority order. Simulations are finally provided for more than 20 agents to emphasize the effectiveness of the proposed interactive approach to multi-agent planning problems.

• The Journal of Korea Robotics Society
• /
• v.5 no.2
• /
• pp.127-134
• /
• 2010

In this paper, a hybrid semi-3D path planning algorithm combining Virtual Tangential Vector(VTV) and fuzzy control is proposed. 3D dynamic environmental factors are reflected to the 2D path planning model, VTV. As a result, the robot can control direction from 2D path planning algorithm VTV and speed as well depending on the fuzzy inputs such as the distance between the robot and obstacle, roughness and slope. Performances and feasibilities of the suggested method are demonstrated by using Matlab simulations. Simulation results show that fuzzy rules and obstacle avoidance methods are working properly toward virtual 3D environments. The proposed hybrid semi-3D path planning is expected to be well applicable to a real life environment, considering its simplicity and realistic nature of the dynamic factors included.

• Journal of the Korean Society for Precision Engineering
• /
• v.26 no.9
• /
• pp.45-52
• /
• 2009

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.10a
• /
• pp.131-134
• /
• 2005

This paper presents a computer-aided simulation and robotic-assisted execution technology of external fixation method to achieve fracture reduction and deformity correction in long bones. Combining the kinematic analysis with a graphic model of the tibia and the fixator allowed 3D simulation and visualization of the adjustments required to reduce fracture or correct bone deformity as a pre-operative planning tool. The developed robot model provided accurate deformity correction with small residual deformity based on the results of the planning. By incorporating the robot model with image-guided system and computer-aided planning, the integrated system could be useful for computer-aided pre-operative planning and robotic-assisted execution in fracture treatment and bone deformity surgery.

• The Journal of Korea Robotics Society
• /
• v.14 no.2
• /
• pp.104-113
• /
• 2019

Object manipulation in cluttered environments remains an open hard problem. In cluttered environments, grasping objects often fails for various reasons. This paper proposes a novel task and motion planning scheme to grasp objects obstructed by other objects in cluttered environments. Task and motion planning (TAMP) aims to generate a sequence of task-level actions where its feasibility is verified in the motion space. The proposed scheme contains an open-loop consisting of three distinct phases: 1) Generation of a task-level skeleton plan with pose references, 2) Instantiation of pose references by motion-level search, and 3) Re-planning task based on the updated state description. By conducting experiments with simulated robots, we show the high efficiency of our scheme.

• The Journal of Korea Robotics Society
• /
• v.16 no.2
• /
• pp.122-129
• /
• 2021

For the Simultaneous Localization and Mapping (SLAM) problem, a different path results in different SLAM results. Usually, SLAM follows a trail of input data. Active SLAM, which determines where to sense for the next step, can suggest a better path for a better SLAM result during the data acquisition step. In this paper, we will use reinforcement learning to find where to perceive. By assigning entire target area coverage to a goal and uncertainty as a negative reward, the reinforcement learning network finds an optimal path to minimize trajectory uncertainty and maximize map coverage. However, most active SLAM researches are performed in indoor or aerial environments where robots can move in every direction. In the urban environment, vehicles only can move following road structure and traffic rules. Graph structure can efficiently express road environment, considering crossroads and streets as nodes and edges, respectively. In this paper, we propose a novel method to find optimal SLAM path using graph structure and reinforcement learning technique.

• The Journal of Korea Robotics Society
• /
• v.17 no.3
• /
• pp.303-307
• /
• 2022

This paper proposes a method that can generate a smooth trajectory from the discontinuous trajectory in kinematic, dynamic, and task-space trajectory constraints. The problem is defined as the minimization of kinetic energy, and then the simulation is performed by using the MATLAB. Kinematic and inverse kinematic equations are derived for the simulation of the 6-DOF robotic arm. The simulation results showed that the trajectory of each joint is generated while satisfying the constraints without any discontinuity. There are small errors in the Cartesian trajectory, but unnecessary deceleration and acceleration can be eliminated. In addition, it is possible to quickly switch between the robotic tasks by applying the proposed method.

• The Journal of Korea Robotics Society
• /
• v.18 no.3
• /
• pp.316-322
• /
• 2023

The increasing popularity of autonomous unmanned aerial vehicles (UAVs) can be attributed to their wide range of applications. 3D path planning is one of the crucial components enabling autonomous flight. In this paper, we present a novel 3D path planning algorithm that generates and utilizes curvature-based trajectories. Our approach leverages circular properties, offering notable advantages. First, circular trajectories make collision detection easier. Second, the planning procedure is streamlined by eliminating the need for the spline process to generate dynamically feasible trajectories. To validate our proposed algorithm, we conducted simulations in Gazebo Simulator. Within the simulation, we placed various obstacles such as pillars, nets, trees, and walls. The results demonstrate the efficacy and potential of our proposed algorithm in facilitating efficient and reliable 3D path planning for UAVs.