Path constrained time-optimal motion of a cooperative two robot system

Robotica ◽  
1995 ◽  
Vol 13 (4) ◽  
pp. 363-374 ◽  
Author(s):  
Hye-Kyung Cho ◽  
Bum-Hee Lee ◽  
Myoung-Sam Ko
Keyword(s):  
Motion Planning ◽  
Optimal Solution ◽  
Problem Formulation ◽  
Planning Problem ◽  
Optimal Motion ◽  
Robot System ◽  
Admissible Region ◽  
Time Motion ◽  
State Dependent ◽  
Time Optimal

SummaryThis paper presents a systematic approach to the time-optimal motion planning of a cooperative two robot system along a prescribed path. First, the minimum-time motion planning problem is formulated in a concise form by parameterizing the dynamics of the robot system through a single variable describing the path. The constraints imposed on the input actuator torques and the exerted forces on the object are then converted into those on that variable, which result in the so-called admissible region in the phase plane of the variable. Considering the load distribution problem that is also involved in the motion, we present a systematic method to construct the admissible region by employing the orthogonal projection technique and the theory of multiple objective optimization. Especially, the effects of viscous damping and state-dependent actuator bounds are incorporated into the problem formulation so that the case where the admissible region is not simply connected can be investigated in detail. The resultant time-optimal solution specifies not only the velocity profile, but also the force assigned to each robot at each instant. Physical interpretation on the characteristics of the optimal actuator torques is also included with computer simulation results.

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.

Optimal Motion Planning Approach for Mobile Robot Navigation Problem

2015 ◽  
Vol 799-800 ◽  
pp. 1078-1082
Author(s):  
Bashra Kadhim Oleiwi ◽  
Hubert Roth ◽  
Bahaa I. Kazem
Keyword(s):  
Motion Planning ◽  
Mobile Robots ◽  
Spline Interpolation ◽  
Optimal Solution ◽  
Mobile Robot Navigation ◽  
Optimal Motion ◽  
Navigation Problem ◽  
Modified Genetic Algorithm ◽  
Planning Approach ◽  
Optimal Motion Planning

In this study, modified genetic algorithm (MGA) and A* search method (A*) is proposed for optimal motion planning of mobile robots. MGA utilizes the classical search and modified A* to establish a sub-optimal collision-free path as initial solution in simple and complex static environment. The enhancements for the proposed approach are presented in initialization stage and enhanced operators. Five objective functions are used to minimize traveling length, time, smoothness, security and trajectory and to reduce the energy consumption for mobile robots by using Cubic Spline interpolation curve fitting for optimal planned path. The purpose of this study is to evaluate the proposed approach performance by taking into consideration the effect of changing the number of iteration (it) and the size of population (pop) on its performance index. The simulation results show the effectiveness of proposed approach in governing the robot’s movements successfully from start to goal point after avoiding all obstacles its way in all tested environment. In addition, the results indicate that the proposed approach can find the optimal solution efficiently in a single run. This approach has been carried out by GUI using a popular engineering programming language, MATLAB.

Task-Constrained Optimal Motion Planning of Redundant Robots Via Sequential Expanded Lagrangian Homotopy

2018 ◽  
Vol 10 (3) ◽  
Author(s):  
Audelia G. Dharmawan ◽  
Shaohui Foong ◽  
Gim Song Soh
Keyword(s):  
Motion Planning ◽  
Real Time ◽  
Dynamic Environment ◽  
Computational Time ◽  
Mobile Manipulator ◽  
Optimal Motion ◽  
Task Constraints ◽  
Moving Obstacles ◽  
Time Motion ◽  
Optimal Motion Planning

Real-time motion planning of robots in a dynamic environment requires a continuous evaluation of the determined trajectory so as to avoid moving obstacles. This is even more challenging when the robot also needs to perform a task optimally while avoiding the obstacles due to the limited time available for generating a new collision-free path. In this paper, we propose the sequential expanded Lagrangian homotopy (SELH) approach, which is capable of determining the globally optimal robot's motion sequentially while satisfying the task constraints. Through numerical simulations, we demonstrate the capabilities of the approach by planning an optimal motion of a redundant mobile manipulator performing a complex trajectory. Comparison against existing optimal motion planning approaches, such as genetic algorithm (GA) and neural network (NN), shows that SELH is able to perform the planning at a faster rate. The considerably short computational time opens up an opportunity to apply this method in real time; and since the robot's motion is planned sequentially, it can also be adjusted to accommodate for dynamically changing constraints such as moving obstacles.

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
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