A Synthetic Algorithm for Tracking a Moving Object in a Multiple‐Dynamic Obstacles Environment Based on Kinematically Planar Redundant Manipulators

Abstract

This paper presents a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators. By observing the motions of the object and obstacles, Spline filter associated with polynomial fitting is utilized to predict their moving paths for a period of time in the future. Several feasible paths for the manipulator in Cartesian space can be planned according to the predicted moving paths and the defined feasibility criterion. The shortest one among these feasible paths is selected as the optimized path. Then the real-time path along the optimized path is planned for the manipulator to track the moving object in real-time. To improve the convergence rate of tracking, a virtual controller based on PD controller is designed to adaptively adjust the real-time path. In the process of tracking, the null space of inverse kinematic and the local rotation coordinate method (LRCM) are utilized for the arms and the end-effector to avoid obstacles, respectively. Finally, the moving object in a multiple-dynamic obstacles environment is thus tracked via real-time updating the joint angles of manipulator according to the iterative method. Simulation results show that the proposed algorithm is feasible to track a moving object in a multiple-dynamic obstacles environment.

Quantized Kalman Filter-Based Pattern Matching for Detection and Tracking of Moving Objects

“…However, this method focuses only at the level of the appearance model and is not focused on object detection. In [10], a synthetic algorithm for tracking a moving object in a multiple-dynamic obstacles environment based on kinematically planar manipulators was introduced. This method is feasible only to track a moving object in a multidynamic obstacle environment.…”

“…Figure 4(a) and (b) shows the two input frames for which pattern matching is performed for identifying the moving objects in video frames. The foreground seed point of the two frames are extracted using functions defined in equations (10) and (11). matching.…”

Real-Time Joint Angular-Acceleration Planning for Vision-Based Kinematically Redundant Manipulator in Dynamic Environment

“…The real-time motion planning methods for robot manipulators has been thoroughly studied in existing literatures and divided into real-time Cartesian motion planning [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20] and real-time joint trajectory planning [21][22][23][24][25][26][27][28][29][30][31][32][33]. Real-time Cartesian motion planning is usually chosen priority because of the intuitive operation/task space, simple description of the path constraints, direct expression of the end-effector (EE) pose, and easy achievement for obstacle avoidance.…”

“…Additionally, force/moment, dynamics model, parameterized processing of velocity and acceleration, and limit of absolute jerk value, are also required in dynamics-based planning [6,11,13], which results in much more highly nonlinear model and tedious calculations. Some real-time planning methods based on kinematics is sample and practical, like fixed proportionbased [16], fixed clamp-based [17], pose error controllerbased [18], and intelligent methods [10,19]. However, these methods consider only position and velocity information in Cartesian space and fluctuations still exist in the path and joint trajectory.…”

“…On the basis of the previous contributions [6,10,11,18,[20][21][22][23][24]33], this paper proposes a simple and practical realtime planning method of angular acceleration in joint configuration spaces based on the kinematics, which can describe the operations tasks and motion constraints of Cartesian space directly in dynamic environment, and obtain smooth trajectories in joint space simultaneously.…”