scholarly journals Trajectory Optimization for Velocity Jumps Reduction considering the Unexpectedness Characteristics of Space Manipulator Joint-Locked Failure

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Qingxuan Jia ◽  
Tong Li ◽  
Gang Chen ◽  
Hanxu Sun ◽  
Jian Zhang
Keyword(s):  
Objective Function ◽  
Trajectory Optimization ◽  
Failure Time ◽  
Null Space ◽  
Joint Space ◽  
Task Completion ◽  
Coefficient Function ◽  
Optimization Strategy ◽  
Space Manipulator ◽  
Optimal Coefficient

Aiming at reducing joint velocity jumps caused by an unexpected joint-locked failure during space manipulator on-orbit operations without shutting down manipulator, trajectory optimization strategy considering the unexpectedness characteristics of joint-locked failure is proposed in the paper, which can achieve velocity jumps reduction in both operation space and joint space simultaneously. In the strategy, velocity in operation space concerning task completion directly is treated as equality constraints, and velocity in joint space concerning motion performance is treated as objective function. Global compensation vector which consists of coefficient, gradient of manipulability, and orthogonal matrix of null space is constructed to minimize the objective function. For each particular failure time, unique optimal coefficient can be obtained when the objective function is minimal. As a basis, a method for optimal coefficient function fitting is proposed based on a priori failure information (possible failure time and the corresponding optimal coefficient) to guarantee the unexpectedness characteristics of joint-locked failure. Simulations are implemented to validate the efficiency of trajectory optimization strategy in reducing velocity jumps in both joint space and operation space. And the feasibility of coefficient function is also verified in reducing velocity jump no matter when joint-locked failure occurs.

Multi-Objective Trajectory Optimization of Free-Floating Space Manipulator Using NSGA-II

2015 ◽  
Vol 713-715 ◽  
pp. 800-804 ◽  
Author(s):  
Gang Chen ◽  
Cong Wei ◽  
Qing Xuan Jia ◽  
Han Xu Sun ◽  
Bo Yang Yu
Keyword(s):  
Trajectory Optimization ◽  
Interpolation Method ◽  
Optimal Solution ◽  
Optimization Method ◽  
Joint Space ◽  
Motion Path ◽  
Objective Functions ◽  
Nsga Ii ◽  
Space Manipulator ◽  
Multi Objective

In this paper, a kind of multi-objective trajectory optimization method based on non-dominated sorting genetic algorithm II (NSGA-II) is proposed for free-floating space manipulator. The aim is to optimize the motion path of the space manipulator with joint angle constraints and joint velocity constraints. Firstly, the kinematics and dynamics model are built. Secondly, the 3-5-3 piecewise polynomial is selected as interpolation method for trajectory planning of joint space. Thirdly, three objective functions are established to simultaneously minimize execution time, energy consumption and jerk of the joints. At last, the objective functions are combined with the NSGA-II algorithm to get the Pareto optimal solution set. The effectiveness of the mentioned method is verified by simulations.

Comparing Online Robot Joint Space Trajectory Optimization for Task Space Applications

2021 ◽  
Author(s):  
Maximilian Kramer ◽  
Rodrigo J. Velasco-Guillen ◽  
Philipp Beckerle ◽  
Torsten Bertram
Keyword(s):  
Trajectory Optimization ◽  
Joint Space ◽  
Task Space ◽  
Space Applications

Trajectory optimization for inhibiting the joint parameter jump of a space manipulator with a load-carrying task

2019 ◽  
Vol 140 ◽  
pp. 59-82 ◽  
Author(s):  
Gang Chen ◽  
Bonan Yuan ◽  
Qingxuan Jia ◽  
Yingzhuo Fu ◽  
Jiayi Tan
Keyword(s):  
Trajectory Optimization ◽  
Space Manipulator ◽  
Load Carrying

Leader–follower-based dynamic trajectory planning for multirobot formation

Robotica ◽  
2013 ◽  
Vol 31 (8) ◽  
pp. 1351-1359 ◽  
Author(s):  
Shuang Liu ◽  
Dong Sun
Keyword(s):  
Analytical Solution ◽  
Objective Function ◽  
Collision Avoidance ◽  
Trajectory Planning ◽  
Trajectory Optimization ◽  
Optimal Trajectory ◽  
Dynamic Environment ◽  
Current Paper ◽  
New Approach ◽  
Dynamic Trajectory

SUMMARYThe present paper presents a new approach to a leader–follower-based dynamic trajectory planning for multirobot formation. A near-optimal trajectory is generated for each robot in a decentralized manner. The main contributions of the current paper are the proposal of a new objective function that considers both collision avoidance and formation requirement for the trajectory generation, and an analytical solution of trajectory parameters in the trajectory optimization. Simulations and experiments on multirobots are performed to demonstrate the effectiveness of the proposed approach to the multirobot formation in a dynamic environment.

Experimental and Novel Analytical Trajectory Optimization of a 7-DOF Baxter Robot: Global Design Sensitivity and Step Size Analyses

2017 ◽  
Author(s):  
Mostafa Bagheri ◽  
Peiman Naseradinmousavi ◽  
Rasha Morsi
Keyword(s):  
Global Optimization ◽  
Cost Function ◽  
Trajectory Optimization ◽  
Computational Cost ◽  
Joint Space ◽  
Design Sensitivity ◽  
Target Object ◽  
Size Analysis ◽  
Step Size ◽  
Novel Approach

In this paper, we present a novel nonlinear analytical coupled trajectory optimization of a 7-DOF Baxter manipulator validated through experimental work utilizing global optimization tools. The robotic manipulators used in network-based applications of industrial units and even homes, for disabled patients, spend significant lumped amount of energy and therefore, optimal trajectories need to be generated to address efficiency issues. We here examine both heuristic (Genetics) and gradient based (GlobalSearch) algorithms for a novel approach of “S-Shaped” trajectory (unlike conventional polynomials), to avoid being trapped in several possible local minima along with yielding minimal computational cost, enforcing operational time and torque saturation constraints. The global schemes are utilized in minimizing the lumped amount of energy consumed in a nominal path given in the collision-free joint space except an impact between the robot’s end effector and a target object for the nominal operation. Note that such robots are typically operated for thousands of cycles resulting in a considerable cost of operation. Due to the expected computational cost of such global optimization algorithms, step size analysis is carried out to minimize both the computational cost (iteration) and possibly cost function by finding an optimal step size. Global design sensitivity analysis is also performed to examine the effects of changes of optimization variables on the cost function defined.

scholarly journals Investigation of Cyclicity of Kinematic Resolution Methods for Serial and Parallel Planar Manipulators

Robotics ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 9
Author(s):  
Maurizio Ruggiu ◽  
Andreas Müller
Keyword(s):  
Objective Function ◽  
Inverse Kinematics ◽  
Joint Space ◽  
Point Of View ◽  
Initial Configuration ◽  
Local Optimum ◽  
Closed Path ◽  
Redundancy Resolution ◽  
Projected Gradient Method ◽  
Inverse Kinematics Problem

Kinematic redundancy of manipulators is a well-understood topic, and various methods were developed for the redundancy resolution in order to solve the inverse kinematics problem, at least for serial manipulators. An important question, with high practical relevance, is whether the inverse kinematics solution is cyclic, i.e., whether the redundancy solution leads to a closed path in joint space as a solution of a closed path in task space. This paper investigates the cyclicity property of two widely used redundancy resolution methods, namely the projected gradient method (PGM) and the augmented Jacobian method (AJM), by means of examples. Both methods determine solutions that minimize an objective function, and from an application point of view, the sensitivity of the methods on the initial configuration is crucial. Numerical results are reported for redundant serial robotic arms and for redundant parallel kinematic manipulators. While the AJM is known to be cyclic, it turns out that also the PGM exhibits cyclicity. However, only the PGM converges to the local optimum of the objective function when starting from an initial configuration of the cyclic trajectory.

Genetic Algorithm for Nanoscale Electro-Thermal Optimization

2007 ◽  
Author(s):  
Adam W. Skorek ◽  
Anna Gryko-Nikitin ◽  
Joanicjusz Nazarko
Keyword(s):  
Genetic Algorithm ◽  
Heat Source ◽  
Objective Function ◽  
Optimization Algorithm ◽  
Specific Function ◽  
Optimization Strategy ◽  
Thermal Optimization

In this paper, we are presenting a genetic algorithm adopted for electro-thermal optimization in nanoelectronics devices and systems. The model of nanoelectronic system is simplified. Each heat source will be approximated by a specific function. The presented optimization strategy is designated for any system containing a number N of nanoelectronic elements. Optimization for the overall structure of the system will be performed in conformity with the temperature minimization criteria in the chosen areas of the system. Regarding others non unexpected modifications of the optimization algorithm, we are using a modified complex objective function.

Design and Optimization of Multiple Microchannel Heat Transfer Systems Based on Multiple Prioritized Preferences

2012 ◽  
Author(s):  
Po Ting Lin ◽  
Jingru Zhang ◽  
Yogesh Jaluria ◽  
Hae Chang Gea
Keyword(s):  
Heat Transfer ◽  
Objective Function ◽  
Optimal Solution ◽  
Optimization Strategy ◽  
Pressure Drops ◽  
Design And Optimization ◽  
Heat Flows ◽  
First Case ◽  
Efficiency Measures ◽  
Objective Function Values

Multiple microchannel heat transfer systems have been developed for the urge of rapid and effective cooling of the electronic devices, which have become smaller and more powerful but also produced more heat. Two different types of single-phase liquid cooling, including the straight and U-shaped microchannel heat sinks, have been utilized to reduce the temperature of the electronic chips. The cooling performances however depend on the preferences of different factors such as the thermal resistances, the pressure drops, and the heat flows at the solid-fluid interfaces. Lower thermal resistance represents higher temperature reduction; lower pressure drop means lower usage of the pumping power; and higher heat flows indicates more effective cooling between the heat spreader and the liquid. In this paper, an optimization strategy based on the prioritized performances has been developed to find the optimal design variables for multiple objectives: minimal thermal resistances, minimal pressure drops and maximal heat flows. The fuzzy and correlated preferences are modeled by the Gaussian membership functions with respect to different levels of the objective function values. The overall performances are formulated based on the prioritized preferences and maximized on the Pareto-optimal solution set to find the solutions for various preference conditions. Two case studies have been discussed. The first case considered the prioritized preferences based on uni-objective function values while the second one focused on the preferences of the thermal resistances and the efficiency measures, correlatively evaluated by the flow rates, pressure drops, and heat flows.

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