Trajectory Planning Using Artificial Potential Fields with Metaheuristics

Batista, José Eduardo; Souza, Darielson A.; Silva, Fernando; Ramos, Kaio Martins; Costa, Jonatha Rodrigues da; Reis, Laurinda L. N. dos; Braga, Arthur P. S.

doi:10.1109/tla.2020.9082920

Cited by 30 publications

(25 citation statements)

References 23 publications

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“…The lengths (l) and mass values (m) of each joint of the manipulator are shown in the Table 1. arm) [16], [17]. A minimal kinematic parameterization of the manipulator according to the well-known Denavit-Hartenberg (DH) in [18] is established and presented in Table 2.…”

Section: Characteristics Of the Manipulatormentioning

confidence: 99%

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Pid and LQR Controllers Applied to the Inverse Dynamics of a 3-Dof Manipulator

Batista¹,

Souza²,

Reis³

et al. 2021

bjdv

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The application in the industrial manipulator robots has grown over the years making production systems increasingly efficient. Within this context, the need for efficient controllers is required to perform the control of these manipulators. In this work the PID controller (Proportional-Integral-Derivative) and LQR (Linear Quadratic Regulator) is presented from the inverse dynamics model of a RPP (Rotational - Prismatic - Prismatic) cylindrical manipulator. The inverse dynamic model which is modeled on Simulink together with a cascaded PID controller is presented. The PID and LQR results are also presented for joint independent and joint dependent control, i.e a controlled PID is used for each joint, controlling the trajectories and speeds at the same time. This paper has as main contributions the development of the manipulator dynamics model and the design of the LQR and PID controllers applied to the inverse dynamics model, which makes the system simpler to control.

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Section: Characteristics Of the Manipulatormentioning

confidence: 99%

“…Then the formulation based on the Lagrangian method was applied for the final calculation. [17]. From the Lagrange equation ( 2), the equations of the movements of each joint can be determined, as can be seen below…”

Section: Dynamic Model Of the Cylindrical Manipulatormentioning

confidence: 99%

Pid and LQR Controllers Applied to the Inverse Dynamics of a 3-Dof Manipulator

Batista¹,

Souza²,

Reis³

et al. 2021

bjdv

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show abstract

“…Para a elaboração eficaz de rotas é necessário o uso de algoritmos, os quais possibilitarão a leitura da área de trabalho da máquina e a identificação dos obstáculos (Batista et al, 2020b).…”

Section: Introductionunclassified

Prevenção De Colisão De Um Manipulador Scara Utilizando Campos Potenciais Artificiais E Caminhos Probabilísticos / Collision Avoidance of a Scara Manipulator Using Potential Artificial Fields and Probabilistic Roadmap

Dias

Silva

Batista

et al. 2021

BJD

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“…Trajectory planning consists of determining a curve in the workspace, connecting the desired, initial and final position of the actuator, avoiding any obstacle. The union of positions in the Cartesian space defines two types of profiles for linear and circular displacements (Khatib, 1986), (Batista et al, 2020b), (Batista et al, 2018).…”

Section: Introductionmentioning

confidence: 99%

Path Planning Collision Avoidance using Reinforcement Learning

Batista

Vasconcelos

Ramos

et al. 2020

Anais Do Congresso Brasileiro De Automática 2020

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Industrial robots have grown over the years making production systems more and more efficient, requiring the need for efficient trajectory generation algorithms that optimize and, if possible, generate collision-free trajectories without interrupting the production process. In this work is presented the use of Reinforcement Learning (RL), based on the Q-Learning algorithm, in the trajectory generation of a robotic manipulator and also a comparison of its use with and without constraints of the manipulator kinematics, in order to generate collisionfree trajectories. The results of the simulations are presented with respect to the efficiency of the algorithm and its use in trajectory generation, a comparison of the computational cost for the use of constraints is also presented.

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Trajectory Planning Using Artificial Potential Fields with Metaheuristics

Cited by 30 publications

References 23 publications

Pid and LQR Controllers Applied to the Inverse Dynamics of a 3-Dof Manipulator

Pid and LQR Controllers Applied to the Inverse Dynamics of a 3-Dof Manipulator

Prevenção De Colisão De Um Manipulador Scara Utilizando Campos Potenciais Artificiais E Caminhos Probabilísticos / Collision Avoidance of a Scara Manipulator Using Potential Artificial Fields and Probabilistic Roadmap

Path Planning Collision Avoidance using Reinforcement Learning

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