An approach for smooth trajectory planning of high-speed pick-and-place parallel robots using quintic B-splines

Abstract

2018) An approach for smooth trajectory planning of high-speed pick-and-place parallel robots using quintic B-splines. Mechanism and Machine Theory,. A note on versions:The version presented here may differ from the published version or, version of record, if you wish to cite this item you are advised to consult the publisher's version. Please see the 'permanent WRAP url' above for details on accessing the published version and note that access may require a subscription.For more information, please contact the WRAP Abstract: This paper presents a new, highly effective approach for optimal smooth trajectory planning of high-speed pick-and-place parallel robots. The pick-and-place path is decomposed into two orthogonal coordinate axes in the Cartesian space and quintic B-spline curves are used to generate the motion profile along each axis for achieving C 4 -continuity. By using symmetrical properties of the geometric path defined, the proposed motion profile becomes essentially dominated by two key factors, representing the ratios of the time intervals for the end-effector to move from the initial point to the adjacent virtual and/or the via-points on the path. These two factors can then be determined by maximizing a weighted sum of two normalized single-objective functions and expressed by curve fitting as functions of the width/height ratio of the pick-and-place path, so allowing them to be stored in a look-up table to enable real-time implementation. Experimental results on a 4-DOF SCARA type parallel robot show that the residual vibration of the end-effector can be substantially reduced thanks to the very continuous and smooth joint torques obtained.

Optimal Trajectory Planning of Grinding Robot Based on Improved Whale Optimization Algorithm

“…In [21], a combination of the modified potential field and numerical approach-based Jacobian to achieve path planning of a redundant robot is proposed. An improved B-spline curve is proposed, which made the angular velocity and angular acceleration smooth and continuous during trajectory movement, and the path of the robot end-effector in the Cartesian space is improved while guaranteeing the smoothness of joint movement [22]. Cubic spline is used to interpolate trajectories to ensure the continuity of jerk in [14].…”

Trajectory Planning and Optimization for a Par4 Parallel Robot Based on Energy Consumption

“…The pick-up span can be computed from the pick-and-place endpoint coordinates, and the pick-up height can be set at an appropriate value by the user. Then, according to the current distances from Wolf ω to Wolf α, Wolf β and Wolf δ, namely D 1 , D 2 , and D 3 , respectively, as shown in Figure 3, we can calculate the likely location of the prey by Equations (28)- (31), which falls within the range of Radius r in Figure 4, representing the possible optimal value range of parameters e and f in the trajectory planning of the Par4 parallel robot. Then, we substitute the obtained optimal e and f values into the gate-shaped path formula which has been planned above, and the corresponding minimum mechanical energy consumption is obtained by following the fifth-order or sixth-order polynomial motion law.…”

“…High-speed pick-and-place operation is one of the main working modes of parallel robots [30,31], and a gate-shaped trajectory is usually adopted, as shown in Figure 1. In the figure, A and H are the pick-and-place endpoints, B, C, E, F and G the intermediate points on the pick-and-place track, H a is the vertical displacement, also known as pick-up height, and B a is the horizontal displacement, also known as pick-up span.…”

Repetitive Control Scheme of Robotic Manipulators Based on Improved B‐Spline Function

“…In [24], higherorder B-splines are applied to the motion planning of serial manipulators. In [25], the acceleration and velocity signal trajectories of rigid link parallel robot are identified and optimized by using quintic B-spline. In [26], spline function is used to optimize the reference input signal of servo driver, and its parameters are determined by particle swarm optimization algorithm, in order to reduce tracking error.…”