A Study on the Development of Underwater Robot Control System for Autonomous Grasping

2020 ◽  
Vol 15 (1) ◽  
pp. 39-47 ◽  
Author(s):  
Yoongeon Lee ◽  
◽  
Yeongjun Lee ◽  
Junbo Chae ◽  
Hyun-Taek Choi ◽  
...  
Keyword(s):  
Control System ◽  
Robot Control ◽  
Underwater Robot ◽  
Robot Control System

Design of Underwater Robot Control System Based on STM32F407

2021 ◽  
pp. 1216-1223
Author(s):  
Zhang Dongsheng ◽  
Wu Hao ◽  
Guan zhiguang ◽  
Zhao lingyan
Keyword(s):  
Control System ◽  
Robot Control ◽  
Underwater Robot ◽  
Robot Control System

A Prototype Wireless Underwater Robot Control system using a 32 kHz Bandwidth Underwater Small Area Acoustic Network (USAAN)

2019 ◽  
Author(s):  
Shiho Oshiro ◽  
Taisaku Suzuki ◽  
Tomohisa Wada ◽  
Yuta Sakima ◽  
Ryuki Chibana ◽  
...  
Keyword(s):  
Control System ◽  
Small Area ◽  
Robot Control ◽  
Underwater Robot ◽  
Robot Control System

Modular design of small underwater robot control system

2021 ◽  
Author(s):  
Hao Wu ◽  
Dongsheng Zhang ◽  
Zhiguang Guan
Keyword(s):  
Control System ◽  
Robot Control ◽  
Modular Design ◽  
Underwater Robot ◽  
Robot Control System

scholarly journals Control system of 4-DOF palletizing robot based on improved R control multi-objective trajectory planning

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110027
Author(s):  
Jianqiang Wang ◽  
Yanmin Zhang ◽  
Xintong Liu
Keyword(s):  
Control System ◽  
Trajectory Planning ◽  
Robot Control ◽  
Machining Process ◽  
Planning System ◽  
Positioning Accuracy ◽  
Multi Objective ◽  
Planning Algorithm ◽  
Function Testing ◽  
Robot Control System

To realize efficient palletizing robot trajectory planning and ensure ultimate robot control system universality and extensibility, the B-spline trajectory planning algorithm is used to establish a palletizing robot control system and the system is tested and analyzed. Simultaneously, to improve trajectory planning speeds, R control trajectory planning is used. Through improved algorithm design, a trajectory interpolation algorithm is established. The robot control system is based on R-dominated multi-objective trajectory planning. System stack function testing and system accuracy testing are conducted in a production environment. During palletizing function testing, the system’s single-step code packet time is stable at approximately 5.8 s and the average evolutionary algebra for each layer ranges between 32.49 and 45.66, which can save trajectory planning time. During system accuracy testing, the palletizing robot system’s repeated positioning accuracy is tested. The repeated positioning accuracy error is currently 10−1 mm and is mainly caused by friction and the machining process. By studying the control system of a four-degrees-of-freedom (4-DOF) palletizing robot based on the trajectory planning algorithm, the design predictions and effects are realized, thus providing a reference for more efficient future palletizing robot design. Although the working process still has some shortcomings, the research has major practical significance.

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