Power optimization of planar redundant manipulator moving along constrained-end trajectory using hybrid techniques

Elshabasy, Mohamed; Mohamed, Khaled T.; Ata, Atef A.

doi:10.1016/j.aej.2017.01.040

Cited by 10 publications

(7 citation statements)

References 22 publications

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“…[23] Proposed optimization using hybrid technique utilize Crossover, Mutation PSO along with interior point method. In 2017 [22] stated a Hybrid method consisting of GA and Fmincon to improve the trajectory optimization for redundant manipulators. In [60] a simulation interface in Delmia robotic environment proposed to solve TO problem.…”

Section: Discussionmentioning

confidence: 99%

“…Stationary Robots: This type of robot is installed in fixed place. Mainly, there is an arm can manipulate around the fixed part of the robot [13][14][15][16][17][18][19][20][21][22][23];…”

Section: Classification According To the Type Of Locomotion Of The Robot Systemsmentioning

confidence: 99%

“…An unbounded number of applications use the techniques of trajectory generation aiming to speculate, plane and formalize the optimum path especially in robotics applications which are the subject of this research. Important applications in robotics such as the robots that use legs [1][2][3][4], navigation robots [5][6][7][8][9][10][11][12] and robot's manipulators [13][14][15][16][17][18][19][20][21][22][23] are in dire need of using the techniques of optimal trajectory in order to optimize the usage of these applications according to the estimates of peripheral conditions.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Almasri¹,

Mk²

2021

Preprint

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Trajectory Optimization (TO) is the sequence of processes that are considered in order to produce the best path that mends the overall performance or reduces the consumption of the resources where the restriction system remains maintained. In this survey, an inclusive review of the latest advancements in modeling and optimization of trajectory generation in robotic applications will be discussed broadly. In recent times, numerous studies have employed optimal control techniques involving direct and indirect methods in order to convert the authentic Trajectory Optimization problem into a constrained parameter optimization problem. Moreover, a huge variety of optimization algorithms such as Genetic Algorithms (GA), Simulated Annealing (SA), Sequential Quadratic Programming (SQP), and Particle Swarm Optimization (PSO) are used aiming to find the optimal solutions for trajectory planning. It is observable that, minimizing the jerk, energy consumption, and execution time among the most widely used design objectives, on the other hand, the robot’s joints configurations and the motor torques are the most used design variables. This paper aims to review the fundamental techniques and their coincident robotic applications in the field of trajectory optimization aiming to afford some steering for related researchers.

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Section: Discussionmentioning

confidence: 99%

“…Stationary Robots: This type of robot is installed in fixed place. Mainly, there is an arm can manipulate around the fixed part of the robot [13][14][15][16][17][18][19][20][21][22][23];…”

Section: Classification According To the Type Of Locomotion Of The Robot Systemsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Almasri¹,

Mk²

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…Many heuristic search-based trajectory planning researches aiming at energy saving have been proposed. Elshabasy et al [22] developed a redundant manipulator trajectory planning method based on the combination of genetic algorithm and constrained function with the consideration of minimum energy consumption. However, with the motion stability not taken into consideration, the jerks of the joints might increase dramatically so it is not suitable for large manipulators.…”

Section: Introductionmentioning

confidence: 99%

Trajectory planning of large redundant manipulator considering kinematic constraints and energy efficiency

Liu,

Huang,

Liu

et al. 2023

Robotica

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For the large redundant manipulator, due to its long working distance and large mass, the number of links (i.e., manipulator’s arms) that can be driven to move simultaneously is limited. Otherwise, the control accuracy and motion stability of the manipulator will deteriorate. Focusing on that, a weighted Newton iteration (WNI) algorithm for trajectory planning of the manipulator is firstly proposed, where the motion of the manipulator joints is controlled by a weight matrix, which is constant and related to each link’s energy consumption. To dynamically adjust the weight matrix according to kinematic constraints and acquire better energy efficiency, an adaptive WNI (AWNI) algorithm is further proposed. In AWNI, the weight matrix is adjusted in real-time during the planning process, with considerations of the kinematic constraints and the energy consumption of the manipulator. The switch of the links between the working state and the non-working state is made through the weight matrix to achieve flexible control of the manipulator motion. Two evaluation functions are established to validate the effectiveness of AWNI in energy saving and motion stability control. Taking a 6 degrees of freedom (DOF) manipulator as an example, simulation experiments on trajectory planning are carried out and the results show the effectiveness of the proposed AWNI algorithm.

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“…These methods involve a function known as a fitness or objective function. Its purpose is to refine the angles of joints continuously; the solution to redundancy resolution is to maximize the objective value [27]. In this case, the objective function is not limited to kinematic control and can generate different random configurations within and outside the kinematic model; this optimization-driven approach changes the paradigm to solve the redundancy resolution of robotic manipulators.…”

Section: Introductionmentioning

confidence: 99%

Evolutionary Computation Based Real-time Robot Arm Path-planning Using Beetle Antennae Search

Khan

Cao

et al. 2022

EAI Endorsed Trans AI Robotics

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This paper presents a model-free real-time kinematic tracking controller for a redundant manipulator. Redundant manipulators are common in industrial applications because of the flexibility and dexterity they get from redundant joints. However, at the same time, the modeling of these systems becomes quite challenging, even for simple tasks like trajectory tracking. Some classical approaches are being used to tackle the issue, including a numerical approximation of the Jacobian and pseudo-inverse of the Jacobian matrix. These approaches have their limitations as they require exact parameters for the modeling of the manipulator; they are not immune to position error accumulation with time and put the manipulator way off the target position. Swarm-based meta-heuristic algorithms have given a new direction to the solution of the redundancy resolution problem. However, they are computationally intensive, formulated in discrete-time, and better suited for offline computation rather than real-time. We proposed a novel continuous-time Zeroing Neural Network with Beetle Antennae Search (ZNNBAS). The ZNNBAS algorithm can solve the quadratic optimization problem for redundancy resolution in real-time. To test its performance, we applied it on 7-DOF redundant manipulator with two trajectories to follow: character ``M" and hypotrochoid. The manipulator was able to trace the reference trajectories with minimal tracking errors.

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Power optimization of planar redundant manipulator moving along constrained-end trajectory using hybrid techniques

Cited by 10 publications

References 22 publications

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Trajectory planning of large redundant manipulator considering kinematic constraints and energy efficiency

Evolutionary Computation Based Real-time Robot Arm Path-planning Using Beetle Antennae Search

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