• Journal of Institute of Control, Robotics and Systems
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• v.17 no.4
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• pp.362-367
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• 2011

The collision-free path of a manipulator should be regenerated in the real time to achieve collision safety when obstacles or humans come into the workspace of the manipulator. A probabilistic roadmap (PRM) method, one of the popular path planning schemes for a manipulator, can find a collision-free path by connecting the start and goal poses through the roadmap constructed by drawing random nodes in the free configuration space. The path planning method based on the configuration space shows robust performance for static environments which can be converted into the off-line processing. However, since this method spends considerable time on converting dynamic obstacles into the configuration space, it is not appropriate for real-time generation of a collision-free path. On the other hand, the method based on the workspace can provide fast response even for dynamic environments because it does not need the conversion into the configuration space. In this paper, we propose an efficient real-time path planning by combining the PRM and the potential field methods to cope with static and dynamic environments. The PRM can generate a collision-free path and the potential field method can determine the configuration of the manipulator. A series of experiments show that the proposed path planning method can provide robust performance for various obstacles.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.4 s.175
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• pp.848-857
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• 2000

A pick-and-place operation in 3-dimensional environment is basic operation for human and multi-purpose manipulators. However, there may be a difficult problem for such manipulators. Especially, if the object cannot be moved with a single grasp, regrasping, which can be a time-consuming process, should be carried out. Regrasping, given initial and final pose of the target object, is a construction of sequential transition of object poses that are compatible with two poses in the point of grasp configuration. This paper presents a novel approach for solving regrasp problem. The approach consists of a preprocessing and a planning stage. Preprocessing, which is done only once for a given robot, generates a look-up table which has information of kinematically feasible task space of end-effector through all the workspace. Then, using the table planning automatically determines possible intermediate location, pose and regrasp sequence leading from the pick-up to put-down grasp. Experiments show that the presented is complete in the total workspace. The regrasp planner was combined with existing path.

• The Journal of Korea Robotics Society
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• v.2 no.3
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• pp.275-281
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• 2007

This paper presents a motion planning strategy for legged robots using locomotion primitives in the complex 3D environments. First, we define configuration, motion primitives and locomotion primitives for legged robots. A hierarchical motion planning method based on a combination of 2.5 dimensional maps of the 3D workspace is proposed. A global navigation map is obtained using 2.5 dimensional maps such as an obstacle height map, a passage map, and a gradient map of obstacles to distinguish obstacles. A high-level path planner finds a global path from a 2D navigation map. A mid-level planner creates sub-goals that help the legged robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. A local obstacle map that describes the edge or border of the obstacles is used to find the sub-goals along the global path. A low-level planner searches for a feasible sequence of locomotion primitives between sub-goals. We use heuristic algorithm in local motion planner. The proposed planning method is verified by both locomotion and soccer experiments on a small biped robot in a cluttered environment. Experiment results show an improvement in motion stability.

• Proceedings of the KIEE Conference
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• 1990.07a
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• pp.492-495
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• 1990

This paper introduces a path planning technique for a mobile robot in the presence of obstacles. In the technique, workspace is described by regional graph and represented obstacles by the three-layer neural network. And performance cost is defined under consideration both the traveling distance and the safety of a mobile robot. Then a collision-free path is obtained using the neural optimization technique.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.04a
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• pp.7-10
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• 2007

This paper presents a fuzzy footstep planner for humanoid robots in complex environments. First, we define locomotion primitives for humanoid robots. A global planner finds a global path from a navigation map that is generated based on a combination of 2.5 dimensional maps of the 3D workspace. A local planner searches for an optimal sequence of locomotion primitives along the global path by using fuzzy footstep planning. We verify our approach on a virtual humanoid robot in a simulated environment. Simulation results show a reduction in planning time and the feasibility of the proposed method.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.42-52
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• 2006

In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.2
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• pp.101-107
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• 2014

Mobile robots use an environment map of its workspace to complete the surveillance task. However grid-based maps that are commonly used map format for mobile robot navigation use a large size of memory for accurate representation of environment. In this reason, grid-based maps are not suitable for path planning of mobile robots using embedded board. In this paper, we present the path planning algorithm that produce a secure path rapidly. The proposed approach utilizes a hybrid map that uses less memory than grid map and has same efficiency of a topological map. Experimental results show that the fast path planning uses only 1.5% of the time that a grid map based path planning requires. And the results show a secure path for mobile robot.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.4
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• pp.350-356
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• 2004

This paper presents a farce manipulability analysis of multi-legged walking robots, which calculates force or acceleration workspace attainable from joint torque limits of each leg. Based on the observation that the kinematic structure of the multi-legged walking robots is basically the same as that of multiple cooperating robots, we derive the proposed method of analyzing the force manipulability of walking robot. The force acting on the object in multiple cooperating robot systems is taken as reaction force from ground to each robot foot in multi-legged walking robots, which is converted to the force of the body of walking robot by the nature of the reaction force. Note that each joint torque in multiple cooperating robot systems is transformed to the workspace of force or acceleration of the object manipulated by the robots in task space through the Jacobian matrix and grasp matrix. Assuming the torque limits are given in infinite norm-sense, the resultant dynamic manipulability is derived as a polytope. The validity of proposed method is verified by several examples, and the proposed method is believed to be useful for the optimal posture planning and gait planning of walking robots.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10b
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• pp.990-995
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• 1990

A minimum-time trajectory planning for two robot arms with designated paths and coordination is proposed. The problem considered in this paper is a subproblem of hierarchically decomposed trajectory planning approach for multiple robots : i) path planning, ii) coordination planning, iii) velocity planning. In coordination planning stage, coordination space, a specific form of configuration space, is constructed to determine collision region and collision-free region, and a collision-free coordination curve (CFCC) passing collision-free region is selected. In velocity planning stage, normal dynamic equations of the robots, described by joint angles, velocities and accelerations, are converted into simpler forms which are described by traveling distance along collision-free coordination curve. By utilizing maximum allowable torques and joint velocity limits, admissible range of velocity and acceleration along CFCC is derived, and a minimum-time velocity planning is calculated in phase plane. Also the planning algorithm itself is converted to simple numerical iterative calculation form based on the concept of neural optimization network, which gives a feasible approximate solution to this planning problem. To show the usefulness of proposed method, an example of trajectory planning for 2 SCARA type robots in common workspace is illustrated.

• The Journal of Korea Robotics Society
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• v.3 no.2
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• pp.137-145
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• 2008

We present the initial results of on-going research for building a novel Mobile Haptic Interface (MHI) that can provide an unlimited haptic workspace in large immersive virtual environments. When a user explores a large virtual environment, the MHI can sense the position and orientation of the user, place itself to an appropriate configuration, and deliver force feedback, thereby enabling a virtually limitless workspace. Our MHI (PoMHI v0.5) features with omnidirectional mobility, a collision-free motion planning algorithm, and force feedback for general environment models. We also provide experimental results that show the fidelity of our mobile haptic interface.