• Journal of Electrical Engineering and information Science
• /
• 제2권3호
• /
• pp.51-60
• /
• 1997

A practically applicable collision free trajectory planning technique for tow robot systems is proposed. The robot trajectories considered in this work are composed of many segments, an at the intersection points between segments robots stop to assemble, weld, ordo other jobs by the attached a end-effectors. The proposed method is based on the Planning-Coordination Decomposition where planning is to find a trajectory of each robot independently according to their tasks and coordination is to find a velocity modification profile to avoid collision with each other. To fully utilize the independently planned trajectories and to ensure no geometrical path deviation after coordination, we develop a simple technique added the minimal delay time to avoid collision just before moving along path segments. We determine the least delay time by the graphical method in the Coordination space where collisions and coordinations are easily visualized. We classify all possible cases into 3 group and derive the optimal solution for each group.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
• /
• pp.168-171
• /
• 1993

In this paper, we design a time optimal controller of a dual arm robot to handle the object. Differently from the master-slave type robot, same priority is imposed on the both of the arms for effective handling the specifed object. For finding a time optimal collision-free trajectory, a graphical method is applied for the robot with two degree of freedom. Some simulation results show the effectiveness of the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제18권7호
• /
• pp.1726-1748
• /
• 2024

Trajectory planning is vital for autonomous systems like robotics and UAVs, as it determines optimal, safe paths considering physical limitations, environmental factors, and agent interactions. Recent advancements in trajectory planning and future location prediction stem from rapid progress in machine learning and optimization algorithms. In this paper, we proposed a novel framework for Spatial-temporal transformer-based feed-forward neural networks (STTFFNs). From the traffic flow local area point of view, skip-gram model is trained on trajectory data to generate embeddings that capture the high-level features of different trajectories. These embeddings can then be used as input to a transformer-based trajectory planning model, which can generate trajectories for new objects based on the embeddings of similar trajectories in the training data. In the next step, distant regions, we embedded feedforward network is responsible for generating the distant trajectories by taking as input a set of features that represent the object's current state and historical data. One advantage of using feedforward networks for distant trajectory planning is their ability to capture long-term dependencies in the data. In the final step of forecasting for future locations, the encoder and decoder are crucial parts of the proposed technique. Spatial destinations are encoded utilizing location-based social networks(LBSN) based on visiting semantic locations. The model has been specially trained to forecast future locations using precise longitude and latitude values. Following rigorous testing on two real-world datasets, Porto and Manhattan, it was discovered that the model outperformed a prediction accuracy of 8.7% previous state-of-the-art methods.

• 한국정밀공학회지
• /
• 제23권7호
• /
• pp.84-92
• /
• 2006

This paper deals with determination of motions of a humanoid robot using genetic algorithm. A humanoid robot has some problems of the structural instability basically. So, we have to consider the stable walking gait in gait planning. Besides, it is important to make the smoothly optimal gait for saving the electric power. A mobile robot has battery to move autonomously. But a humanoid robot needs more electric power in order to drive many joints. So, if movements of walking joint don't maintain optimally, it is hard to sustain the battery power during the working period. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. Also, if a gait trajectory doesn't have optimal state, the expected lift span of joints tends to be decreased. To solve these problems, the genetic algorithm is employed to guarantee the optimal gait trajectory. The fitness functions in a genetic algorithm are introduced to find out optimal trajectory, which enables the robot to have the less reduced jerk of joints and get smooth movement. With these all process accomplished by PC-based program, the optimal solution could be obtained from the simulation. In addition, we discuss the design consideration fur the joint motion and distributed computation of tile humanoid, ISHURO, and suggest its result such as structure of the network and a disturbance observer.

• International Journal of Aeronautical and Space Sciences
• /
• 제8권1호
• /
• pp.54-65
• /
• 2007

Parameter optimization technique is applied to planning UAVs(Unmanned Aerial Vehicles) path under artificial enemy radar threats. The ground enemy radar threats are characterized in terms of RCS(Radar Cross Section) parameter which is a measure of exposure to the radar threats. Mathematical model of the RCS parameter is constructed by a simple mathematical function in the three-dimensional space. The RCS model is directly linked to the UAVs attitude angles in generating a desired trajectory by reducing the RCS parameter. The RCS parameter is explicitly included in a performance index for optimization. The resultant UAVs trajectory satisfies geometrical boundary conditions while minimizing a weighted combination of the flight time and the measure of ground radar threat expressed in RCS.

• 제어로봇시스템학회지
• /
• 제1권1호
• /
• pp.16-16
• /
• 1995

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• Transactions on Control, Automation and Systems Engineering
• /
• 제1권1호
• /
• pp.16-20
• /
• 1999

Like the usual systems, the industrial robot manipulator has some constraints for motion. Usually we hope that the manipulators move fast to accomplish the given task. The problem can be formulated as the time-optimal control problem under the constraints such as the limits of velocity, acceleration and jerk. But it is very difficult to obtain the exact solution of the time-optimal control problem. This paper solves this problem in two steps. In the first step, we find the minimum time trajectories by optimizing cubic polynomial joint trajectories under the physical constraints using the modified evolution strategy. In the second step, the controller is optimized for robot manipulator to track precisely the optimized trajectory found in the previous step. Experimental results for SCARA type manipulator show that the proposed method is very useful.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1996년도 추계학술대회 논문집
• /
• pp.406-412
• /
• 1996

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumption in a fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of penalty area is newly introduced and this penalty area is included in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• 한국정밀공학회지
• /
• 제14권3호
• /
• pp.147-155
• /
• 1997

Optimal trajectory for a robot manipulator minimizing actuator torques or energy consumptions ina fixed traveling time is obtained in the presence of obstacles. All joint displacements are represented in finite terms of Fourier cosine series and the coefficients of the series are obtained optimally by nonlinear programming. Thus, the geometric path need not be prespecified and the full dynamic model is employed. To avoid the obstacles, the concept of the penalty area is newly introduced and this penalty area is includ- ed in the performance index with an appropriate weighting coefficient. This optimal trajectory will be useful as a geometric path in the minimum-time trajectory planning problem.

• International Journal of Control, Automation, and Systems
• /
• 제6권3호
• /
• pp.401-412
• /
• 2008

This paper discusses a design methodology of cooperative path planning for dynamical multi-agent systems with spatial and temporal constraints. The cooperative behavior of the multi-agent systems is specified in terms of the objective function in an optimization formulation. The path of achieving cooperative tasks is then generated by the optimization formulation constructed based on a differential flatness approach. Three scenarios of multi-agent tasking are proposed at the cooperative task planning framework. Given agent dynamics, both spatial and temporal constraints are considered in the path planning. The path planning algorithm first finds trajectory curves in a lower-dimensional space and then parameterizes the curves by a set of B-spline representations. The coefficients of the B-spline curves are further solved by a sequential quadratic programming solver to achieve the optimization objective and satisfy these constraints. Finally, several illustrative examples of cooperative path/task planning are presented.