• Journal of information and communication convergence engineering
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• v.11 no.4
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• pp.274-281
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• 2013

In this study, we consider the challenges in motion planning for automated driving systems. Most of the existing online motion-planning algorithms, which take dynamics into account, find it difficult to operate in an environment with narrow passages. Some of the existing algorithms overcome this by offline preprocessing if environment is known. In this work an online algorithm for motion planning with dynamics in an unknown cluttered environment with narrow passages is presented. It utilizes an idea of hybrid planning with sampling- and discretization-based motion planners, which run simultaneously in a full configuration space and a derived reduced space. The proposed algorithm has been implemented and tested with a real autonomous vehicle. It provides significant improvements in computational time performance over basic planning algorithms and allows the generation of smoother paths than those generated by the recently developed hybrid motion planners.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.217-226
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• 2006

Grasping and manipulation by hands can be considered as one of inevitable functions to achieve the performances desired in humanoid operations. When a humanoid robot manipulates an object by his hands, each finger should be well-controlled to accomplish a precise manipulation of the object grasped. So, the trajectory of each joint required for a precise finger motion is fundamentally necessary to be planned stably. In this sense, this paper proposes an effective joint motion planning method for humanoid fingers. The proposed method newly employs a bio-mimetic concept for joint motion planning. A suitable model that describes an interphalangeal coordination in a human finger is suggested and incorporated into the proposed joint motion planning method. The feature of the proposed method is illustrated by simulation results. As a result, the proposed method is useful for a facilitative finger motion. It can be applied to improve the control performance of humanoid fingers or prosthetic fingers.

• The Journal of Korea Robotics Society
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• v.16 no.3
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• pp.283-290
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• 2021

We propose a task and motion planning algorithm for clearing obstacles and wiping surfaces, which is essential for surface disinfection during the pathogen disinfection process. The proposed task and motion planning algorithm determines task parameters such as grasping pose and placement location during the planning process without using pre-specified or discretized values. Furthermore, to quickly inspect many unit motions, we propose a motion feasibility prediction algorithm consisting of collision checking and an SVM model for inverse mechanics and self-collision prediction. Planning time analysis shows that the feasibility prediction algorithm can significantly increase the planning speed and success rates in situations with multiple obstacles. Finally, we implemented a hierarchical control scheme to enable wiping motion while following a planner-generated joint trajectory. We verified our planning and control framework by conducted an obstacle-clearing and surface wiping experiment in a simulated disinfection environment.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.428-433
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• 1993

An analytic solution approach to the time-varying obstacle avoidance problem is pursued. We use the view-time concept, especially the adaptive view-time. First. we introduce the adaptive view-time and analyze its properties. Next, we propose a view-time based motion planning method. The proposed method is applied and simulated for the collision-free motion planning of a 2 DOF robot manipulator. We simulate the robot motion under several different view-time systems. Generally, the motion planning with the adaptive view-time systems has some advantages over that with the fixed view-time systems.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.388-393
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• 1990

A robot manipulator and an obstacle are described mathematically in joint space, with the mathematical representation for the collision between the robot manipulator and the obstacle. Using these descriptions, the robot motion planning problem is formulated which can be used to avoide a time varying obstacle. To solve the problem, the constraints on motion planning are discretized in joint space. An analytical method is proposed for planning the motion in joint space from a given starting point to the goal point. It is found that solving the inverse kinematics problem is not necessary to get the control input to the joint motion controller for collision avoidance.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.37.3-37
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• 2002

$\textbullet$ Mobile robots $\textbullet$ Sensor-based motion planning $\textbullet$ Potential field $\textbullet$ Local minimum-free motion $\textbullet$ Virtual target point $\textbullet$ Set of linked line segments $\textbullet$ We build a sensor-based motion planning using virtual target point for free of local minimum

• Journal of information and communication convergence engineering
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• v.12 no.2
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• pp.116-121
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• 2014

This paper discusses computer-generated heuristics for motion planning. Planning with many degrees of freedom is a challenging task, because the complexity of most planning algorithms grows exponentially with the number of dimensions of the problem. A well-designed heuristic may greatly improve the performance of a planning algorithm in terms of the computation time. However, in recent years, with increasingly challenging high-dimensional planning problems, the design of good heuristics has itself become a complicated task. In this paper, we present an approach to algorithmically develop a heuristic for motion planning, which increases the efficiency of a planner in similar environments. To implement the idea, we generalize modern motion planning algorithms to an extent, where a heuristic is represented as a set of random variables. Distributions of the variables are then analyzed with computer learning methods. The analysis results are then utilized to generate a heuristic. During the experiments, the proposed approach is applied to several planning tasks with different algorithms and is shown to improve performance.

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

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1374-1381
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• 2022

Under the influence of nuclear radiation, the reliability of steam generators (SGs) is an important factor in the efficiency and safety of nuclear power plant (NPP) reactors. Motion planning that remotely manipulates an SG mobile tube-inspection robot to inspect SG heat transfer tubes is the mainstream trend of NPP robot development. To achieve motion planning, conditional traversal is usually used for base position optimization, and then the A^* algorithm is used for path planning. However, the proposed approach requires considerable processing time and has a single expansion during path planning and plan paths with many turns, which decreases the working speed of the robot. Therefore, to reduce the calculation time and improve the efficiency of motion planning, modifications such as the matrix method, improved parent node, turning cost, and improved expanded node were proposed in this study. We also present a comprehensive evaluation index to evaluate the performance of the improved algorithm. We validated the efficiency of the proposed method by planning on a tube sheet with square-type tube arrays and experimenting with Model SG.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.500-507
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• 2022

In this study, a motion planning method based on the integer representation of contact status between wheels and the ground is proposed for planning swing motion of a 6×6 wheel-legged robot to cross large obstacles and gaps. Wheel-legged robots can drive on a flat road by wheels and overcome large obstacles by legs. Autonomously crossing large obstacles requires the robot to perform complex motion planning of multi-contacts and wheel-rolling at the same time. The lift-off and touch-down status of wheels and the trajectories of legs should be carefully planned to avoid collision between the robot body and the obstacle. To address this issue, we propose a planning method for swing motion of robot legs. It combines an integer representation of discrete contact status and a trajectory optimization based on the direct collocation method, which results in a mixed-integer nonlinear programming (MINLP) problem. The planned motion is used to control the joint angles of the articulated legs. The proposed method is verified by the MuJoCo simulation and shows that over 95% and 83% success rate when the height of vertical obstacles and the length of gaps are equal to or less than 1.68 times of the wheel radius and 1.44 times of the wheel diameter, respectively.