scholarly journals Trajectory planning for mobile manipulators with vibration reduction

2021 ◽  
Author(s):  
Grzegorz Pajak
Keyword(s):  
Trajectory Planning ◽  
Vibration Reduction ◽  
Mobile Manipulators

On Control of Flexible Mobile Manipulators: Positioning and Vibration Reduction Using an Eye-in-Hand Range Camera

1998 ◽  
Vol 31 (3) ◽  
pp. 619-625
Author(s):  
Bernt Nilsson ◽  
Jonas Nygårds ◽  
Ulf Larsson ◽  
Åke Wernersson
Keyword(s):  
Vibration Reduction ◽  
Mobile Manipulators ◽  
Range Camera

Control of flexible mobile manipulators: positioning and vibration reduction using an eye-in-hand range camera

1999 ◽  
Vol 7 (6) ◽  
pp. 741-751 ◽  
Author(s):  
Bernt Nilsson ◽  
Jonas Nygårds ◽  
Ulf Larsson ◽  
Åke Wernersson
Keyword(s):  
Vibration Reduction ◽  
Mobile Manipulators ◽  
Range Camera

Trajectory planning of mobile manipulators using dynamic programming approach

Robotica ◽  
2012 ◽  
Vol 31 (4) ◽  
pp. 643-656 ◽  
Author(s):  
M. H. Korayem ◽  
M. Irani ◽  
A. Charesaz ◽  
A. H. Korayem ◽  
A. Hashemi
Keyword(s):  
Dynamic Programming ◽  
Trajectory Planning ◽  
Optimal Trajectory ◽  
Vision System ◽  
Optimal Path ◽  
Optimization Method ◽  
Mobile Manipulator ◽  
Programming Approach ◽  
Planning Problem ◽  
Mobile Manipulators

SUMMARYThis paper presents a solution for optimal trajectory planning problem of robotic manipulators with complicated dynamic equations. The main goal is to find the optimal path with maximum dynamic load carrying capacity (DLCC). Proposed method can be implemented to problems of both motion along a specified path and point-to-point motion. Dynamic Programming (DP) approach is applied to solve optimization problem and find the positions and velocities that minimize a pre-defined performance index. Unlike previous attempts, proposed method increases the speed of convergence by using the sequential quadratic programming (SQP) formulation. This formulation is used for solving problems with nonlinear constraints. Also, this paper proposes a new algorithm to design optimal trajectory with maximum DLCC for both fixed and mobile base mechanical manipulators. Algorithms for DLCC calculations in previous works were based on indirect optimization method or linear programming approach. The proposed trajectory planning method is applied to a linear tracked Puma and the mobile manipulator named Scout. Application of this algorithm is confirmed and simulation results are compared with experimental results for Scout robot. In experimental test, results are obtained using a new stereo vision system to determine the position of the robot end-effector.

Vibration reduction of delta robot based on trajectory planning

2020 ◽  
Vol 153 ◽  
pp. 104004 ◽  
Author(s):  
Mingkun Wu ◽  
Jiangping Mei ◽  
Yanqin Zhao ◽  
Wentie Niu
Keyword(s):  
Trajectory Planning ◽  
Vibration Reduction ◽  
Delta Robot

scholarly journals Point-to-Point Collision-Free Trajectory Planning for Mobile Manipulators

2016 ◽  
Vol 85 (3-4) ◽  
pp. 523-538 ◽  
Author(s):  
Grzegorz Pajak ◽  
Iwona Pajak
Keyword(s):  
Collision Avoidance ◽  
Trajectory Planning ◽  
Three Dimensional ◽  
Nonholonomic Constraints ◽  
Inequality Constraints ◽  
Mobile Manipulator ◽  
Local Perturbation ◽  
Mobile Manipulators ◽  
State Variables ◽  
Mechanical Constraints

AbstractThe collision-free trajectory planning method subject to control constraints for mobile manipulators is presented. The robot task is to move from the current configuration to a given final position in the workspace. The motions are planned in order to maximise an instantaneous manipulability measure to avoid manipulator singularities. Inequality constraints on state variables i.e. collision avoidance conditions and mechanical constraints are taken into consideration. The collision avoidance is accomplished by local perturbation of the mobile manipulator motion in the obstacles neighbourhood. The fulfilment of mechanical constraints is ensured by using a penalty function approach. The proposed method guarantees satisfying control limitations resulting from capabilities of robot actuators by applying the trajectory scaling approach. Nonholonomic constraints in a Pfaffian form are explicitly incorporated into the control algorithm. A computer example involving a mobile manipulator consisting of nonholonomic platform (2,0) class and 3DOF RPR type holonomic manipulator operating in a three-dimensional task space is also presented.

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