IMU-Based Online Kinematic Calibration of Robot Manipulator

Robot calibration is a useful diagnostic method for improving the positioning accuracy in robot production and maintenance. An online robot self-calibration method based on inertial measurement unit (IMU) is presented in this paper. The method requires that the IMU is rigidly attached to the robot manipulator, which makes it possible to obtain the orientation of the manipulator with the orientation of the IMU in real time. This paper proposed an efficient approach which incorporates Factored Quaternion Algorithm (FQA) and Kalman Filter (KF) to estimate the orientation of the IMU. Then, an Extended Kalman Filter (EKF) is used to estimate kinematic parameter errors. Using this proposed orientation estimation method will result in improved reliability and accuracy in determining the orientation of the manipulator. Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. Experimental studies on a GOOGOL GRB3016 robot show that this method has better accuracy, convenience, and effectiveness than vision-based methods

Active Collision Avoidance for Human-Robot Interaction With UKF, Expert System, and Artificial Potential Field Method

With the development of Industry 4.0, the cooperation between robots and people is increasing. Therefore, man—machine security is the first problem that must be solved. In this paper, we proposed a novel methodology of active collision avoidance to safeguard the human who enters the robot's workspace. In the conventional approaches of obstacle avoidance, it is not easy for robots and humans to work safely in the common unstructured environment due to the lack of the intelligence. In this system, one Kinect is employed to monitor the workspace of the robot and detect anyone who enters the workspace of the robot. Once someone enters the working space, the human will be detected, and the skeleton of the human can be calculated in real time by the Kinect. The measurement errors increase over time, owing to the tracking error and the noise of the device. Therefore we use an Unscented Kalman Filter (UKF) to estimate the positions of the skeleton points. We employ an expert system to estimate the behavior of the human. Then let the robot avoid the human by taking different measures, such as stopping, bypassing the human or getting away. Finally, when the robot needs to execute bypassing the human in real time, to achieve this, we adopt a method called artificial potential field method to generate a new path for the robot. By using this active collision avoidance, the system can achieve the purpose that the robot is unable to touch on the human. This proposed system highlights the advantage that during the process, it can first detect the human, then analyze the motion of the human and finally safeguard the human. We experimentally tested the active collision avoidance system in real-world applications. The results of the test indicate that it can effectively ensure human security

Human-Manipulator Interface Using Hybrid Sensors via CMAC for Dual Robots

This paper presents a novel method that allows a human operator to communicate his motion to the dual robot manipulators by performing his two double hand-arms movements, which would naturally carry out an object manipulation task. The proposed method uses hybrid sensors to obtain the position and orientation of the human hands. Although the position and the orientation of the human can be obtained from the sensors, the measurement errors increase over time due to the noise of the devices and the tracking error. A cerebellar model articulation controller (CMAC) is used to estimate the position and orientation of the human hand. Due to the limitations of the perceptive and the motor, human operator can not accomplish the high precision manipulation without any assistant. An adaptive multi-space transformation (AMT) is employed to assist the operator to improve the accuracy and reliability in determining the pose of the manipulator. With making full use of the human hand-arms motion, the operator would feel kind of immersive. Using this human-robot interface, the object manipulation task done in collaboration by dual robots could be carried out flexibly through preferring the double hand-arms motion by one operator

Meta-analysis of antiviral protection of white spot syndrome virus vaccine to the shrimp

Currently, white spot syndrome virus (WSSV) is one of the most serious pathogens that impacts shrimp farming around the world. A WSSV vaccine provides a significant protective benefit to the host shrimp. Although various types of vaccines against WSSV have emerged, the immune effects among them were not compared, and it remains unclear which type of vaccine has the strongest protective effect. Meanwhile, due to the lack of effective routes of administration and immunization programs, WSSV vaccines have been greatly limited in the actual shrimp farming. To answer these questions, this study conducted a comprehensive meta-analysis over dozens of studies and compared all types WSSV vaccines, which include sub-unit protein vaccines, whole virus inactivated vaccines, DNA vaccines and RNA-based vaccines. The results showed that the RNA-based vaccine had the highest protection rate over the other three types of vaccines. Among the various sub-unit protein vaccines, VP26 vaccine had the best protective effects than other sub-unit protein vaccines. Moreover, this study demonstrated that vaccines expressed in eukaryotic hosts had higher protection rates than that of prokaryotic systems. Among the three immunization modes (oral administration, immersion and injection) used in monovalent protein vaccines, oral administration had the highest protection rate. In natural conditions, shrimp are mostly infected by the virus orally. These results provide a guide for exploration of a novel WSSV vaccine and help facilitate the application of WSSV vaccines in shrimp farming

A Novel Flexible Virtual Fixtures for Teleoperation

This paper proposed a novel spatial-motion-constraints virtual fixtures (VFs) method for the human-machine interface collaborative technique. In our method, two 3D flexible VFs have been presented: warning pipe and safe pipe. And a potential-collision-detection method based on two flexible VFs has been proposed. The safe pipe constructs the safe workspace dynamically for the robot, which makes it possible to detect the potential collision between the robot and the obstacles. By calculating the speed and the acceleration of the robot end-effecter (EE), the warning pipe can adjust its radius to detect the deviation from the EE to the reference path. These spatial constraints serve as constraint conditions for constrained robot control. The approach enables multiobstacle manipulation task of telerobot in precise interactive teleoperation environment. We illustrate our approach on a teleoperative manipulation task and analyze the performance results. The performance-comparison experimental results demonstrate that the control mode employing our method can assist the operator more precisely in teleoperative tasks. Due to the properties such as collision avoidance and safety, operators can complete the tasks more efficiently along with reduction in operating tension

Human-Manipulator Interface Using Particle Filter

This paper utilizes a human-robot interface system which incorporates particle filter (PF) and adaptive multispace transformation (AMT) to track the pose of the human hand for controlling the robot manipulator. This system employs a 3D camera (Kinect) to determine the orientation and the translation of the human hand. We use Camshift algorithm to track the hand. PF is used to estimate the translation of the human hand. Although a PF is used for estimating the translation, the translation error increases in a short period of time when the sensors fail to detect the hand motion. Therefore, a methodology to correct the translation error is required. What is more, to be subject to the perceptive limitations and the motor limitations, human operator is hard to carry out the high precision operation. This paper proposes an adaptive multispace transformation (AMT) method to assist the operator to improve the accuracy and reliability in determining the pose of the robot. The human-robot interface system was experimentally tested in a lab environment, and the results indicate that such a system can successfully control a robot manipulator

Markerless Kinect-Based Hand Tracking for Robot Teleoperation

This paper presents a real-time remote robot teleoperation method using markerless Kinect-based hand tracking. Using this tracking algorithm, the positions of index finger and thumb in 3D can be estimated by processing depth images from Kinect. The hand pose is used as a model to specify the pose of a real-time remote robot's end-effector. This method provides a way to send a whole task to a remote robot instead of sending limited motion commands like gesture-based approaches and this method has been tested in pick-and-place tasks