End-Effector Stabilization of a 10-DOF Mobile Manipulator using Nonlinear Model Predictive Control

Osman, Mostafa; Mehrez, Mohamed W.; Yang, Shiyi; Jeon, Soo; Melek, William

doi:10.1016/j.ifacol.2020.12.2658

Cited by 9 publications

(4 citation statements)

References 16 publications

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“…Despite excessive wind velocity, the controller generates the adequate smooth control actions guaranteeing that the steady state error that converges towards values close to zero with the dependency of the external disturbances. The use of CasADI such as an optimization framework guarantees the fact that the computational time always stays below the sample time, which is one of main problems in NMPC schemes due to the highly computational time that these solutions required, as similar computing times were presented in [45].…”

Section: Discussionmentioning

confidence: 99%

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

Recalde

Guevara

Carvajal

et al. 2022

Sensors

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Accurate trajectory tracking is a critical property of unmanned aerial vehicles (UAVs) due to system nonlinearities, under-actuated properties and constraints. Specifically, the use of unmanned rotorcrafts with accuracy trajectory tracking controllers in dynamic environments has the potential to improve the fields of environment monitoring, safety, search and rescue, border surveillance, geology and mining, agriculture industry, and traffic control. Monitoring operations in dynamic environments produce significant complications with respect to accuracy and obstacles in the surrounding environment and, in many cases, it is difficult to perform even with state-of-the-art controllers. This work presents a nonlinear model predictive control (NMPC) with collision avoidance for hexacopters’ trajectory tracking in dynamic environments, as well as shows a comparative study between the accuracies of the Euler–Lagrange formulation and the dynamic mode decomposition (DMD) models in order to find the precise representation of the system dynamics. The proposed controller includes limits on the maneuverability velocities, system dynamics, obstacles and the tracking error in the optimization control problem (OCP). In order to show the good performance of this control proposal, computational simulations and real experiments were carried out using a six rotary-wind unmanned aerial vehicle (hexacopter—DJI MATRICE 600). The experimental results prove the good performance of the predictive scheme and its ability to regenerate the optimal control policy. Simulation results expand the proposed controller in simulating highly dynamic environments that showing the scalability of the controller.

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Section: Discussionmentioning

confidence: 99%

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

Recalde

Guevara

Carvajal

et al. 2022

Sensors

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show abstract

“…In the first three lessons, we intended the agent to acquire basic manipulation abilities to continuously track a set of target positions with specific orientations. In practical usage scenarios, manipulators are often combined with mobile platforms for broader applications ( Osman et al, 2020 ). In contrast to the stationary case, in such scenarios, the influences of the environment should be learned, such as perturbations.…”

Section: Curriculum-sac Learningmentioning

confidence: 99%

Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator

Nakano

et al. 2023

Front. Robot. AI

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A high degree of freedom (DOF) benefits manipulators by presenting various postures when reaching a target. Using a tendon-driven system with an underactuated structure can provide flexibility and weight reduction to such manipulators. The design and control of such a composite system are challenging owing to its complicated architecture and modeling difficulties. In our previous study, we developed a tendon-driven, high-DOF underactuated manipulator inspired from an ostrich neck referred to as the Robostrich arm. This study particularly focused on the control problems and simulation development of such a tendon-driven high-DOF underactuated manipulator. We proposed a curriculum-based reinforcement-learning approach. Inspired by human learning, progressing from simple to complex tasks, the Robostrich arm can obtain manipulation abilities by step-by-step reinforcement learning ranging from simple position control tasks to practical application tasks. In addition, an approach was developed to simulate tendon-driven manipulation with a complicated structure. The results show that the Robostrich arm can continuously reach various targets and simultaneously maintain its tip at the desired orientation while mounted on a mobile platform in the presence of perturbation. These results show that our system can achieve flexible manipulation ability even if vibrations are presented by locomotion.

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“…However, an agriculture robot is also required to have a hand as the substitute for a farmer's hand [11]- [14]. Thus, a mobile manipulator is the most appropriate type of robot applied in agriculture [4][7][16]- [19].…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Logic Controller Application for Automatic Charging System Design of a Solar Powered Mobile Manipulator

2021

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Agriculture is a vital industry that affects the livelihoods of many people. Given the reduction in agricultural employees and the increasing strain on farmers, this sector requires convenience, which the automation system may provide. One of the automations is mobile manipulator implementation to substitute farmers. This study investigates the automatic battery charging system supported by the Fuzzy Logic Controller (FLC) to power a mobile manipulator. The application of solar charging is an ideal power source for the robot applied in the open field with high irradiance all year long. This charging system is equipped with IoT monitoring online to monitor the available power produced by solar panel and the battery capacity condition. The effectiveness of the proposed method is proven by experiments conducted for ten times charging in ten days, where the highest power produced by the panel is 1.080 W with 0.563 W charged to the battery. The highest irradiance comes with the highest surface panel temperature of 58.9OC at the irradiance rate of 1021 W/m2. The experimental results show the possibility of the solar-powered robot, which is ideal for agriculture implementation.

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End-Effector Stabilization of a 10-DOF Mobile Manipulator using Nonlinear Model Predictive Control

Cited by 9 publications

References 16 publications

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

System Identification and Nonlinear Model Predictive Control with Collision Avoidance Applied in Hexacopters UAVs

Curriculum-reinforcement learning on simulation platform of tendon-driven high-degree of freedom underactuated manipulator

Fuzzy Logic Controller Application for Automatic Charging System Design of a Solar Powered Mobile Manipulator

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