Optimization of Arm Manipulator Trajectory Planning in the Presence of Obstacles by Ant Colony Algorithm

Baghli, Fatima Zahra; Bakkali, Larbi El; Lakhal, Yassine

doi:10.1016/j.proeng.2017.02.434

Cited by 29 publications

(11 citation statements)

References 7 publications

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“…In [60] a simulation interface in Delmia robotic environment proposed to solve TO problem. In [65] TO problem solved using Ant Colony algorithm.…”

Section: Discussionmentioning

confidence: 99%

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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“…In [60] a simulation interface in Delmia robotic environment proposed to solve TO problem. In [65] TO problem solved using Ant Colony algorithm.…”

Section: Discussionmentioning

confidence: 99%

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Almasri¹,

Mk²

2021

Preprint

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“…In the field of structural and mechanical engineering, papers have been repetitively published in the last 10 years. Trusses and frames, manufacturing processes, laminated structures (Abachizadeh and Tahani, 2011) and later, smart materials (Abachizadeh et al, 2010), robotics (Baghli et al, 2017) and manufacturing processes (Sankar and Umamaheswara, 2018) are among notable cases optimized using different versions of ant colony algorithms.…”

Section: Ant Colony Optimizationmentioning

confidence: 99%

Tuned mass dampers for the drift reduction of structures with soil effects using ant colony optimization

Soheili

Zoka

Abachizadeh

2020

Advances in Structural Engineering

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This paper probes the effects of the Tuned Mass Damper (TMD) device on the response of a 40-story building including three types of soils and experiencing 16 far-field earthquakes. The Ant Colony Optimization (ACO) method is employed to obtain the best settings for TMD values and the objective is reducing the maximum drift of the structure considering soil structure interaction (SSI) effects. The TMD effects on the displacement and acceleration response of the structure as well as its influence on the drift response are studied. Moreover, the frequency analyses of the drift responses in addition to the story locations with the highest drifts are also investigated. It is shown that the optimized design results in considerable reduction in drifts enhancing the profits of utilizing the TMD device.

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“…In the last few decades, several algorithm have been used to determine collision-free paths, and some of the most common are as follows: (a) sampling-based planning algorithms such as rapidly random trees (RRT) [ 16 ], probabilistic roadmap (PRM) [ 1 , 17 ], and the variants of each of them [ 16 ]; (b) graph-based algorithms such as visibility graph [ 18 ] and A* [ 19 ]; (c) heuristic-based algorithms such as ant colony [ 20 ] and genetic-based [ 3 ]; (d) deterministic-based methods, which include artificial potential fields (APFs) [ 21 ] and the homotopy-based path-planning method (HPPM) [ 22 , 23 , 24 ]. These algorithms and methods have been applied in mobile terrestrial robots, UAVs, car-like vehicles, and robotic manipulators [ 1 , 16 , 17 , 20 , 23 , 25 , 26 , 27 , 28 ]. However, these algorithms and methods still have several drawbacks such as falling into local minima, high computational cost, or long times to obtain a solution path, and some of these do not guarantee a solution path.…”

Section: Introductionmentioning

confidence: 99%

A Novel Collision-Free Homotopy Path Planning for Planar Robotic Arms

Velez-Lopez

Vázquez-Leal

Hernandez-Martinez

et al. 2022

Sensors

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Achieving the smart motion of any autonomous or semi-autonomous robot requires an efficient algorithm to determine a feasible collision-free path. In this paper, a novel collision-free path homotopy-based path-planning algorithm applied to planar robotic arms is presented. The algorithm utilizes homotopy continuation methods (HCMs) to solve the non-linear algebraic equations system (NAES) that models the robot’s workspace. The method was validated with three case studies with robotic arms in different configurations. For the first case, a robot arm with three links must enter a narrow corridor with two obstacles. For the second case, a six-link robot arm with a gripper is required to take an object inside a narrow corridor with two obstacles. For the third case, a twenty-link arm must take an object inside a maze-like environment. These case studies validated, by simulation, the versatility and capacity of the proposed path-planning algorithm. The results show that the CPU time is dozens of milliseconds with a memory consumption less than 4.5 kB for the first two cases. For the third case, the CPU time is around 2.7 s and the memory consumption around 18 kB. Finally, the method’s performance was further validated using the industrial robot arm CRS CataLyst-5 by Thermo Electron.

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Optimization of Arm Manipulator Trajectory Planning in the Presence of Obstacles by Ant Colony Algorithm

Cited by 29 publications

References 7 publications

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Trajectory Optimization in Robotic Applications, Survey of Recent Developments

Tuned mass dampers for the drift reduction of structures with soil effects using ant colony optimization

A Novel Collision-Free Homotopy Path Planning for Planar Robotic Arms

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