首页|Researcher from Shahid Beheshti University Publishes Findings in Robotics (Desig n and development of closed-loop controllers for trajectory tracking of a planar vibration-driven robot)

Researcher from Shahid Beheshti University Publishes Findings in Robotics (Desig n and development of closed-loop controllers for trajectory tracking of a planar vibration-driven robot)

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By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Fresh data on robotics are presented i n a new report. According to news reporting from Tehran, Iran, by NewsRx journal ists, research stated, “Vibration-driven robots constitute an innovative paradig m for achieving locomotion, leveraging periodic vibrations to meticulously contr ol the movement of an internal mass, thus affording them a high degree of precis ion while navigating surfaces with varying friction characteristics.” Our news journalists obtained a quote from the research from Shahid Beheshti Uni versity: “This paper is dedicated to the refinement of trajectory tracking in pl anar vibration-driven robots, achieved through the meticulous design and impleme ntation of a Proportional-Integral-Derivative (PID) controller and Sliding Mode Controller (SMC). The considered vibration-driven robot is propelled using two p arallel reciprocating unbalanced masses which allows the robot to have various m aneuvers in two dimensions. The movement of the robot is improved by employing b ristles to make non-isotropic Coloumb’s friction on the surfaces. At first, the governing dynamic equations of the robot are derived by considering the stick-sl ip effect and using the Euler-Lagrange method. Moreover, a PID controller for ac curate trajectory tracking within the robot’s natural coordinate system is desig ned and employed. The fine-tuning of the PID controller’s coefficients is accomp lished through the application of the NSGA-II optimization method.”

Shahid Beheshti UniversityTehranIranAsiaEmerging TechnologiesMachine LearningNano-robotRobotRobotics

2024

Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
年,卷(期):2024.(Sep.20)