• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.845-848
• /
• 2003

There are many researches on using human neuro-biological signals for various problems such as controlling a mechanical object and/or interfacing human with the computer. It is one of very interesting topics that human can use various instruments without learning specific knowledge if the instruments can be controlled as human intends. In this paper, we proposed an intelligent motion planner for a redundant manipulator, which is controlled by humans neuro-biological signals, especially, EOG (Electrooculogram). We found the optimal motion planner for the redundant manipulator that can move to the desired point. We used neural networks to find the inverse kinematics solution of the manipulator. We also showed the performance of the proposed motion planner with several simulations.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.10 no.3
• /
• pp.203-209
• /
• 2010

This paper presents a hierarchical fuzzy motion planner for humanoid robots in 3D uneven environments. First, we define both motion primitives and locomotion primitives of humanoid robots. A high-level planner finds a global path from a global navigation map that is generated based on a combination of 2.5 dimensional maps of the workspace. We use a passage map, an obstacle map and a gradient map of obstacles to distinguish obstacles. A mid-level planner creates subgoals that help the robot efficiently cope with various obstacles using only a small set of locomotion primitives that are useful for stable navigation of the robot. We use a local obstacle map to find the subgoals along the global path. A low-level planner searches for an optimal sequence of locomotion primitives between subgoals by using fuzzy motion 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.

• Journal of the Korean Society for Precision Engineering
• /
• v.14 no.4
• /
• pp.126-135
• /
• 1997

A sensorless motion planner which succeeds in grasping a polygonal part firmly into a desired orientation has been developed through the dynamic analysis. The analytical results on the impact process with friction are used for modeling the contact motionduring the parallel-jaw grasp operation, which is com- posed of the pushing and the squeezing process. The developed planner succeeds in grasping a part into a specified orientation in the face of uncertainties of initial position and orientation of the part, motion direction of the finger, and the physical parameters such as the coefficients of friction and restitution. The motion planner has been fully implemented into a viable package on the computer system, and verified experimentally. The motion of parts is recorded using a high-speed video camera, and then compared to the results of the planner and the graphic simulation results that illustrate the simulated motion of the grasp operation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1995.10a
• /
• pp.530-533
• /
• 1995

This paper deals with the problem of motion planning for a unicycle-like robot. We present a simple local planner for unicycle model, based on an approximation of the desired configuration generated by local holonomic planner that ignores motion constraints. To guarantee a collision avoidance, we propose an inequality constraint, based on the motion analysis with the constant control input and time interval. Consequently, we formulate our problem as the constrained optimization problem and a feedback scheme based on local sensor information is established by simply solving this problem. Through simulations, we confirm the validity and effectiveness of our algorithm.

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

• 제어로봇시스템학회:학술대회논문집
• /
• 2005.06a
• /
• pp.74-79
• /
• 2005

In this paper, we propose a novel approach to decentralized motion planning and conflict-resolution for multiple mobile agents working in an environment with unexpected moving obstacles. Our proposed motion planner has two characteristics. One is a real-time collision prognosis based on modified collision map. Collision map is a famous centralized motion planner with low computation load, and the collision prognosis hands over these characteristics. And the collision prognosis is based on current robots status, maximum robot speeds, maximum robot accelerations, and path information produced from off-line path planning procedure, so it is applicable to motion planner for multiple agents in a dynamic environment. The other characteristic is that motion controller architecture is based on potential field method, which is capable of integrating robot guidance to the goals with collision avoidance. For the architecture, we define virtual obstacles making delay time for collision avoidance from the real-time collision prognosis. Finally the results obtained from realistic simulation of a multi-robot environment with unknown moving obstacles demonstrate safety and efficiency of the proposed method.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.10 no.3
• /
• pp.33-38
• /
• 2011

A cubic spline trajectory planner with arc-length parameter is formulated with estimation by summing up to the 3rd order in Taylor's expansion. The PVAJT motion planning is presented to reduce trajectory calculation time at every cycle time of servo control loop so that it is able to generate cubic spline trajectory in real time. This method can be used to more complex spline trajectory. Several case studies are executed with different values of cycle time and sampling time, and showed the advantages of the PVAJT motion planner. A DSP-based motion controller is designed to implement the PVAJT motion planning.

• International Journal of Control, Automation, and Systems
• /
• v.4 no.3
• /
• pp.318-324
• /
• 2006

The mobile manipulator is expected to work in partially defined or unstructured environments. In our global/local approach to path planning, joint trajectories are generated for a desired Cartesian space path, designed by the global path planner. For a local path planner, inverse kinematics for a redundant system is used. Joint displacement limit for the manipulator links is considered in the motion planner. In an event of failure to obtain feasible trajectories, the task cannot be accomplished. At the point of failure, a deviation in the Cartesian space path is obtained and a replanner gives a new path that would achieve the goal position. To calculate the deviation, a nonlinear optimization problem is formulated and solved by standard Sequential Quadratic Programming (SQP) method.

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

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10a
• /
• pp.254-259
• /
• 1992

In this paper, we propose an optimal method for the tracking a trajectory of the end-effector of flexible robot arms with multiple joints. The proposed method finds joint trajectories and joint torques necessary to produce the desired end-effector motion of flexible manipulator. In inverse kinematics, optimized joint trajectories are computed from elastic equations. In inverse dynamics, joint torques are obtained from the joint equations by using the optimized joint trajectories. The equations of motion using finite element method and virtual work principle are employed. Optimal control is applied to optimize joint trajectories which are computed in inverse kinematics. The simulation of flexible planner manipulator is presented.