Nonconvex Time-Optimal Trajectory Planning for Robot Manipulators

2019 ◽  
Vol 141 (11) ◽  
Author(s):  
Ákos Nagy ◽  
István Vajk
Keyword(s):  
Motion Planning ◽  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Robot Manipulator ◽  
Viscous Friction ◽  
Global Optimum ◽  
Convex Optimization Problem ◽  
Optimal Motion Planning ◽  
Time Optimal ◽  
Active Research

Time-optimal motion-planning has been a topic of active research in the literature for a while. This paper presents a new approach for velocity profile generation, which is a subproblem in motion-planning. In the case of simplified constraints, profile generation can be translated to a convex optimization problem. However, some practical constraints (e.g., velocity-dependent torque, viscous friction) destroy the convexity. The proposed method can obtain the global optimum of the nonconvex optimization problem. The experimental results with a three degrees-of-freedom (DOF) robot manipulator are also presented in this paper.

On the Optimal Robot Manipulator Motion Planning for Solid Freeform Fabrication by Thermal Spraying

1995 ◽  
Author(s):  
J. Rastegar ◽  
Y. Qin ◽  
Q. Tu
Keyword(s):  
Motion Planning ◽  
Robot Manipulator ◽  
Solid Freeform Fabrication ◽  
Thermal Spraying ◽  
Freeform Fabrication ◽  
Novel Approach ◽  
Solid Objects ◽  
Optimal Motion Planning ◽  
Spatial Geometry ◽  
Probabilistic Nature

Abstract A novel approach to optimal robot manipulator motion planning for Solid Freeform Fabrication (SFF) by thermal spraying is presented. In this approach, given the desired spatial geometry of the object, the motion of the spray gun relative to a forming platform is synthesized for minimal masking requirements considering the probabilistic nature of the thermal spraying process. The material build-up rate can be planned to achieve the desired distribution of the physical/material properties within the object volume. Examples of optimal motion planning for the generation of some basic solid objects and computer simulation of the effectiveness of the developed methodology are presented.

OPTIMAL MOTION PLANNING OF A PLANAR PARALLEL MANIPULATOR WITH KINEMATICALLY REDUNDANT DEGREES OF FREEDOM

2016 ◽  
Vol 40 (3) ◽  
pp. 383-397 ◽  
Author(s):  
Bahman Nouri Rahmat Abadi ◽  
Sajjad Taghvaei ◽  
Ramin Vatankhah
Keyword(s):  
Motion Planning ◽  
Feedback Linearization ◽  
Degrees Of Freedom ◽  
Jacobian Matrix ◽  
Redundant Manipulator ◽  
Optimal Motion ◽  
Planar Parallel Manipulator ◽  
Optimal Motion Planning ◽  
Planning Algorithm ◽  
Actuation Method

In this paper, an optimal motion planning algorithm and dynamic modeling of a planar kinematically redundant manipulator are considered. Kinematics of the manipulator is studied, Jacobian matrix is obtained and the dynamic equations are derived using D’Alembert’s principle. Also, a novel actuation method is introduced and applied to the 3-PRPR planar redundant manipulator. In this approach, the velocity of actuators is determined in such a way to minimize the 2-norm of the velocity vector, subjected to the derived kinematic relations as constraints. Having the optimal motion planning, the motion is controlled via a feedback linearization controller. The motion of the manipulator is simulated and the effectiveness of the proposed actuation strategy and the designed controller is investigated.

scholarly journals Path Tracking Algorithms for Non-Convex Waiter Motion Problem

2018 ◽  
Vol 62 (1) ◽  
pp. 16-23
Author(s):  
Ákos Nagy ◽  
Gábor Csorvási ◽  
István Vajk
Keyword(s):  
Motion Planning ◽  
Optimization Problem ◽  
Minimum Energy ◽  
Real Life ◽  
Problem Formulation ◽  
Energy Planning ◽  
Special Area ◽  
Time Optimal ◽  
Motion Problem ◽  
Optimal Approach

Originally, motion planning was concerned with problems such as how to move an object from a start to a goal position without hitting anything. Later, it has extended with complications such as kinematics, dynamics, uncertainties, and also with some optimality purpose such as minimum-time, minimum-energy planning. The paper presents a time-optimal approach for robotic manipulators. A special area of motion planning is the waiter motion problem, in which a tablet is moved from one place to another as fastas possible, avoiding the slip of the object that is placed upon it. The presented method uses the direct transcription approach for the waiter problem, which means a optimization problem is formed in order to obtain a time-optimal control for the robot. Problem formulation is extended with a non-convex jerk constraints to avoid unwanted oscillations during the motion. The possible local and global solver approaches for the presented formulation are discussed, and the waiter motion problem is validated by real-life experimental results with a 6-DoF robotic arm.

Time Optimal Motion Planning and Admittance Control for Cooperative Grasping

2020 ◽  
Vol 5 (2) ◽  
pp. 2216-2223 ◽  
Author(s):  
Dominik Kaserer ◽  
Hubert Gattringer ◽  
Andreas Muller
Keyword(s):  
Motion Planning ◽  
Admittance Control ◽  
Optimal Motion ◽  
Optimal Motion Planning ◽  
Time Optimal

scholarly journals When Probabilistic Shaping Realizes Improper Signaling for Hardware Distortion Mitigation

2020 ◽  
Author(s):  
Sidrah Javed ◽  
Ahmed Elzanaty ◽  
Osama Amin ◽  
Basem Shihada ◽  
Mohamed-Slim Alouini
Keyword(s):  
Monte Carlo ◽  
Communication Systems ◽  
Error Probability ◽  
Degrees Of Freedom ◽  
Optimization Problem ◽  
Rate Performance ◽  
Convex Optimization Problem ◽  
Maximum A Posterior ◽  
The Impact ◽  
Successive Convex Programming

<pre><pre>Hardware distortions (HWD) render drastic effects on the performance of communication systems. They are recently proven to bear asymmetric signatures; and hence can be efficiently mitigated using improper Gaussian signaling (IGS), thanks to its additional design degrees of freedom. Discrete asymmetric signaling (AS) can practically realize the IGS by shaping the signals' geometry or probability. In this paper, we adopt the probabilistic shaping (PS) instead of uniform symbols to mitigate the impact of HWD and derive the optimal maximum a posterior detector. Then, we design the symbols' probabilities to minimize the error rate performance while accommodating the improper nature of HWD. Although the design problem is a non-convex optimization problem, we simplified it using successive convex programming and propose an iterative algorithm. We further present a hybrid shaping (HS) design to gain the combined benefits of both PS and geometric shaping (GS). Finally, extensive numerical results and Monte-Carlo simulations highlight the superiority of the proposed PS over conventional uniform constellation and GS. Both PS and HS achieve substantial improvements over the traditional uniform constellation and GS with up to one order magnitude in error probability and throughput. </pre></pre>

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