机械臂
遥操作
视觉伺服
计算机科学
机器人末端执行器
控制工程
雅可比矩阵与行列式
控制器(灌溉)
运动学
试验台
航天器
机器人学
正方体卫星
工作区
机器人
人工智能
模拟
控制理论(社会学)
工程类
控制(管理)
航空航天工程
经典力学
生物
物理
数学
计算机网络
应用数学
卫星
农学
作者
Dakota L. Wenberg,Michael D. M. Kutzer,Levi DeVries,John Gregory,Michael Sanders,Jin S. Kang
标识
DOI:10.1109/aero47225.2020.9172592
摘要
The use of robotics in space has become common in the last half century of space exploration. However, robotic arms are rarely entrusted to perform large assembly tasks without a human in the loop because of the high cost of the hardware involved. As our presence in space grows, developing advanced autonomous robotic systems may be the way forward as time lags associated with teleoperation can easily cripple future space missions operating beyond earth orbit. This research focuses on the derivation of an autonomous control system for spacecraft assembly applications that blends Jacobian path following and visual servoing. Jacobian path following assumes the environment is well known and plans end effector trajectories whose performance for assembly may suffer in dynamic or uncertain environments. Visual servoing approaches use feedback from an effector attached camera and can avoid dynamic obstacles, but provides no guarantee of success if the sensor cannot keep the goal location in its field of view and often traverses inefficient manipulator trajectories. This work proposes a hybrid approach that combines both approaches to improve the performance of a robotic manipulator in both known and unknown environments. The robotic systems are simulated using the proposed hybrid controller. The hybrid controller is developed in MATLAB using a kinematic simulation of a two degree of freedom robotic arm operating in a single plane with a simplified camera model. Following successful implementation of the simulation, a more complex robotic arm is simulated in 3D space. The controller is integrated into an existing robotic arm platform (UR5 Industrial Manipulator) for a proof of concept. The results of the testing highlights the path and final position of each controller to demonstrate the advantages of each controller individually and the advantages of the hybrid approach. The paper describes the algorithm development and results of analysis and testing.
科研通智能强力驱动
Strongly Powered by AbleSci AI