SDRE controller for motion design of cable-suspended robot with uncertainties and moving obstacles

Behboodi, Ahad; Salehi, Seyedmohammad

doi:10.1088/1757-899x/248/1/012031

Cited by 3 publications

(2 citation statements)

References 14 publications

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“…Additionally, to control the timing and intensity of contraction, EMG activity can be used as the feedback for exoskeleton applications 81 . To further assure robust and reliable joint motion in the cable-driven exoskeletons actuated by such artificial muscles, the proposed control algorithm for cable-driven robots [136][137][138] , such as the one used in Cable-Driven Arm Exoskeleton (CAREX) 139 , must be assessed for future CT-SDEA-driven exoskeletons.…”

Section: Future Directionmentioning

confidence: 99%

An artificial skeletal muscle for use in pediatric rehabilitation robotics

Behboodi

2021

Soft Robotics in Rehabilitation

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This dissertation is dedicated to my grandma, Azizam. Once I started elementary school, she left her hometown, Shiraz, after 50 years living there, to come and take care of me while my mother was at work. I owe her a significant part of my personality, culture, and academic achievements. We shared many wonderful memories, which we could still laugh at last time I was back in Iran, three years ago. I have lost all of them now to Alzheimer's disease.

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Section: Future Directionmentioning

confidence: 99%

An artificial skeletal muscle for use in pediatric rehabilitation robotics

Behboodi

2021

Soft Robotics in Rehabilitation

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“…In the following section, we first investigate the artificial potential field algorithm and then modify this algorithm in Section 3. In [17], the state-dependent Riccati equation (SDRE) algorithm is studied on the motion design of cable-suspended robots with uncertainties and moving obstacles. A method for controlling the tracing of a robot has been developed by the SDRE.…”

Section: Introductionmentioning

confidence: 99%

Obstacle avoidance of mobile robots using modified artificial potential field algorithm

Rostami

Sangaiah

Wang

et al. 2019

J Wireless Com Network

160

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In recent years, topics related to robotics have become one of the researching fields. In the meantime, intelligent mobile robots have great acceptance, but the control and navigation of these devices are very difficult, and the lack of dealing with fixed obstacles and avoiding them, due to safe and secure routing, is the basic requirement of these systems. In this paper, the modified artificial potential field (APF) method is proposed for that robot avoids collision with fixed obstacles and reaches the target in an optimal path; using this algorithm, the robot can run to the target in optimal environments without any problems by avoiding obstacles, and also using this algorithm, unlike the APF algorithm, the robot does not get stuck in the local minimum. We are looking for an appropriate cost function, with restrictions that we have, and the goal is to avoid obstacles, achieve the target, and do not stop the robot in local minimum. The previous method, APF algorithm, has advantages, such as the use of a simple math model, which is easy to understand and implement. However, this algorithm has many drawbacks; the major drawback of this problem is at the local minimum and the inaccessibility of the target when the obstacles are in the vicinity of the target. Therefore, in order to obtain a better result and to improve the shortcomings of the APF algorithm, this algorithm needs to be improved. Here, the obstacle avoidance planning algorithm is proposed based on the improvement of the artificial potential field algorithm to solve this local minimum problem. In the end, simulation results are evaluated using MATLAB software. The simulation results show that the proposed method is superior to the existing solution.

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