scholarly journals Validation of an IMU-camera fusion algorithm using an industrial robot

2020 ◽  
pp. 101-111
Author(s):  
Gonzalo Perez-Paina ◽  
Claudio Paz ◽  
Martín Pucheta ◽  
Bruno Bianchini ◽  
Fernando Martínez ◽  
...  
Keyword(s):  
Position Control ◽  
Industrial Robot ◽  
Low Cost ◽  
Measurement Unit ◽  
Control Loop ◽  
Fusion Algorithm ◽  
Safe Alternative ◽  
Position And Orientation ◽  
Estimation System ◽  
Set Up

The integration of down-looking camera with an in-ertial measurement unit (IMU) sensor makes possible to provide a lightweight and low-cost pose estimation system for unmanned aerial vehicles (UAVs) and micro-UAVs (MAVs). Recently, the authors developed an algorithm for IMU and exteroceptive sensor fusion filter for position and orientation estimation. The aim of the estimation is to be used in the outer control loop of an UAV for position control. This work presents an experimental set up to test that algorithm using an industrial robot to produce accurate planar trajectories as a safe alternative to testing the algorithm on real UAVs. The results of the IMU-camera fusion estimation for linear positions and linear velocities show an error admissible to be integrated on real UAVs.

scholarly journals A low-cost IMU/GPS position accuracy experimental study using extended kalman filter data fusion in real environments

2021 ◽  
Vol 297 ◽  
pp. 01040
Author(s):  
Aziz El Fatimi ◽  
Adnane Addaim ◽  
Zouhair Guennoun
Keyword(s):  
Experimental Study ◽  
Data Fusion ◽  
Low Cost ◽  
Three Dimensional ◽  
Measurement Unit ◽  
Circular Path ◽  
Positioning System ◽  
Fusion Algorithm ◽  
Position Accuracy ◽  
The Stability

In a three-dimensional environment, the navigation of a vehicle in airspace, terrestrial space, or maritime space presents complex aspects concerning the determination of its position, its orientation, and the stability of the processing of the asynchronous data coming from the various sensors during navigation. In this context, this paper presents an experimental analysis of the position accuracy estimated by a low-cost inertial measurement unit coupled, by the extended Kalman data fusion algorithm, with a system of absolute measurements of a positioning system received from a GPS which designates the global positioning system. The different scenarios of the experimental study carried out during this work concerned three tests in a real environment, such as the navigation in a course inside the city of Rabat/Morocco with a moderate speed, a section on the highway at a speed of 120 Km/h and a circular path around a roundabout. The experimental results proved that the low-cost sensors studied are a good candidate for civil navigation applications.

scholarly journals Modelling and Control of a 2-DOF Robot Arm with Elastic Joints for Safe Human-Robot Interaction

2021 ◽  
Vol 8 ◽  
Author(s):  
Hua Minh Tuan ◽  
Filippo Sanfilippo ◽  
Nguyen Vinh Hao
Keyword(s):  
Control Algorithm ◽  
Position Control ◽  
Low Cost ◽  
Dynamic Environment ◽  
Human Robot Interaction ◽  
Robot Arm ◽  
Control Loop ◽  
Robot Interaction ◽  
Elastic Joint ◽  
Elastic Joints

Collaborative robots (or cobots) are robots that can safely work together or interact with humans in a common space. They gradually become noticeable nowadays. Compliant actuators are very relevant for the design of cobots. This type of actuation scheme mitigates the damage caused by unexpected collision. Therefore, elastic joints are considered to outperform rigid joints when operating in a dynamic environment. However, most of the available elastic robots are relatively costly or difficult to construct. To give researchers a solution that is inexpensive, easily customisable, and fast to fabricate, a newly-designed low-cost, and open-source design of an elastic joint is presented in this work. Based on the newly design elastic joint, a highly-compliant multi-purpose 2-DOF robot arm for safe human-robot interaction is also introduced. The mechanical design of the robot and a position control algorithm are presented. The mechanical prototype is 3D-printed. The control algorithm is a two loops control scheme. In particular, the inner control loop is designed as a model reference adaptive controller (MRAC) to deal with uncertainties in the system parameters, while the outer control loop utilises a fuzzy proportional-integral controller to reduce the effect of external disturbances on the load. The control algorithm is first validated in simulation. Then the effectiveness of the controller is also proven by experiments on the mechanical prototype.

scholarly journals Attitude Determination Method by Fusing Single Antenna GPS and Low Cost MEMS Sensors Using Intelligent Kalman Filter Algorithm

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Lei Wang ◽  
Bo Song ◽  
Xueshuai Han ◽  
Yongping Hao
Keyword(s):  
Kalman Filter ◽  
Attitude Determination ◽  
Fuzzy Controller ◽  
Low Cost ◽  
Transition Process ◽  
Measurement Unit ◽  
Accurate Estimation ◽  
Mems Sensors ◽  
Fusion Algorithm ◽  
Single Antenna

For meeting the demands of cost and size for micronavigation system, a combined attitude determination approach with sensor fusion algorithm and intelligent Kalman filter (IKF) on low cost Micro-Electro-Mechanical System (MEMS) gyroscope, accelerometer, and magnetometer and single antenna Global Positioning System (GPS) is proposed. The effective calibration method is performed to compensate the effect of errors in low cost MEMS Inertial Measurement Unit (IMU). The different control strategies fusing the MEMS multisensors are designed. The yaw angle fusing gyroscope, accelerometer, and magnetometer algorithm is estimated accurately under GPS failure and unavailable sideslip situations. For resolving robust control and characters of the uncertain noise statistics influence, the high gain scale of IKF is adjusted by fuzzy controller in the transition process and steady state to achieve faster convergence and accurate estimation. The experiments comparing different MEMS sensors and fusion algorithms are implemented to verify the validity of the proposed approach.

Design of an Inertial Measuring Unit for Control of Robotic Devices

2019 ◽  
Vol 952 ◽  
pp. 313-322 ◽  
Author(s):  
Emil Škultéty ◽  
Elena Pivarčiová ◽  
Ladislav Karrach
Keyword(s):  
Technology Development ◽  
Industrial Robot ◽  
Low Cost ◽  
Cost Savings ◽  
Industrial Robots ◽  
Measurement Unit ◽  
Mems Sensor ◽  
Wide Range ◽  
Robotic Devices ◽  
Robotic Application

Industrial robots are increasingly used to automate technological processes, such as machining, welding, paint coating, assembly, etc. Automation rationalizes material flows, integrates production facilities and reduces the need for manufacturing inventory, provides cost savings for human maintenance. Technology development and growing competition have an influence on production growth and increase of product quality, and thus the new possibilities in innovation of industrial robot are searched for. One of the possibilities is applying of an inertial navigation system into robot control. This article focuses on new trends in manufacturing technology: design of Inertial Measurement Unit (IMU) for a robotic application control. The Arduino platform is used for the IMU as a hardware solution. The advantage of this platform is low cost and wide range of sensors and devices that are compatible with this platform. For scanning, the MEMS sensor MPU6050 is used, which includes a 3-axis gyroscope and an accelerometer in one chip. New trends in manufacturing facilities, especially robotics innovation and automation, will enable the productivity to grow in production processes.

scholarly journals Terrain Analytics for Precision Agriculture with Automated Vehicle Sensors and Data Fusion

2021 ◽  
Vol 13 (5) ◽  
pp. 2905
Author(s):  
Wei Zhao ◽  
Tianxin Li ◽  
Bozhao Qi ◽  
Qifan Nie ◽  
Troy Runge
Keyword(s):  
Data Fusion ◽  
Precision Agriculture ◽  
Low Cost ◽  
Measurement Unit ◽  
Nutrient Runoff ◽  
Automated Vehicle ◽  
Terrain Attributes ◽  
Simulated Environments ◽  
Set Up ◽  
Vehicle Sensors

Precision agriculture aims to use minimal inputs to generate maximal yields by managing the plant and its environment at a discrete instead of a field level. This new farming methodology requires localized field data including topological terrain attributes, which influence irrigation, field moisture, nutrient runoff, soil compaction, and traction and stability for traversing agriculture machines. Existing research studies have used different sensors, such as distance sensors and cameras, to collect topological information, which may be constrained by energy cost, performance, price, etc. This study proposed a low-cost method to perform farmland topological analytics using sensor implementation and data processing. Inertial measurement unit sensors, which are widely used in automated vehicle study, and a camera are set up on a robot vehicle. Then experiments are conducted under indoor simulated environments that include five common topographies that would be encountered on farms, combined with validation experiments in a real-world field. A data fusion approach was developed and implemented to track robot vehicle movements, monitor the surrounding environment, and finally recognize the topography type in real time. The resulting method was able to clearly recognize topography changes. This low-cost and easy-mount method will be able to augment and calibrate existing mapping algorithms with multidimensional information. Practically, it can also achieve immediate improvement for the operation and path planning of large agricultural machines.

scholarly journals HeadUp: A Low-Cost Solution for Tracking Head Movement of Children with Cerebral Palsy Using IMU

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8148
Author(s):  
Sana Sabah Al-azzawi ◽  
Siavash Khaksar ◽  
Emad Khdhair Hadi ◽  
Himanshu Agrawal ◽  
Iain Murray
Keyword(s):  
Cerebral Palsy ◽  
Low Cost ◽  
Visual Assessment ◽  
Assessment Method ◽  
Measurement Unit ◽  
System Response ◽  
Head Orientation ◽  
Fusion Algorithm ◽  
Ordinary Life ◽  
Head Control

Cerebral palsy (CP) is a common reason for human motor ability limitations caused before birth, through infancy or early childhood. Poor head control is one of the most important problems in children with level IV CP and level V CP, which can affect many aspects of children’s lives. The current visual assessment method for measuring head control ability and cervical range of motion (CROM) lacks accuracy and reliability. In this paper, a HeadUp system that is based on a low-cost, 9-axis, inertial measurement unit (IMU) is proposed to capture and evaluate the head control ability for children with CP. The proposed system wirelessly measures CROM in frontal, sagittal, and transverse planes during ordinary life activities. The system is designed to provide real-time, bidirectional communication with an Euler-based, sensor fusion algorithm (SFA) to estimate the head orientation and its control ability tracking. The experimental results for the proposed SFA show high accuracy in noise reduction with faster system response. The system is clinically tested on five typically developing children and five children with CP (age range: 2–5 years). The proposed HeadUp system can be implemented as a head control trainer in an entertaining way to motivate the child with CP to keep their head up.

Application of the Smart Integrator in the Ship-Borne Radar Servo System

2014 ◽  
Vol 556-562 ◽  
pp. 3287-3290
Author(s):  
Min Tao ◽  
Xin Rong Wang ◽  
Gui Ping Zhang
Keyword(s):  
Resonance Frequency ◽  
Precision Measurement ◽  
Position Control ◽  
Servo System ◽  
Antenna System ◽  
Control Loop ◽  
Set Up

Along with improvement of capability of the precision measurement radar, the servo system with more high capability is needed. A large antenna reduces rigidity and structural resonance frequency of antenna system, and it is even possible to make radar lose the target. Based on analyzing Ship-borne servo system, the model of servo system has been set up and intelligent integral has been applied in the Position Control Loop. The result of simulation shows that this method can decrease overshoot of the servo system and improve the quickness of the servo system.

scholarly journals Enhanced Attitude and Altitude Estimation for Indoor Autonomous UAVs

Drones ◽  
2022 ◽  
Vol 6 (1) ◽  
pp. 18
Author(s):  
Salvatore Rosario Bassolillo ◽  
Egidio D’Amato ◽  
Immacolata Notaro ◽  
Gennaro Ariante ◽  
Giuseppe Del Core ◽  
...  
Keyword(s):  
Low Cost ◽  
Computational Cost ◽  
Estimation Algorithm ◽  
Production Costs ◽  
Measurement Unit ◽  
Fusion Algorithm ◽  
Sensor Platform ◽  
Ultrasonic Ranging ◽  
High Flexibility ◽  
Navigation Accuracy

In recent years the use of Unmanned Aerial Vehicles (UAVs) has considerably grown in the civil sectors, due to their high flexibility of use. Currently, two important key points are making them more and more successful in the civil field, namely the decrease of production costs and the increase in navigation accuracy. In this paper, we propose a Kalman filtering-based sensor fusion algorithm, using a low cost navigation platform that contains an inertial measurement unit (IMU), five ultrasonic ranging sensors and an optical flow camera. The aim is to improve navigation in indoor or GPS-denied environments. A multi-rate version of the Extended Kalman Filter is considered to deal with the use of heterogeneous sensors with different sampling rates, and the presence of non-linearities in the model. The effectiveness of the proposed sensor platform is evaluated by means of numerical tests on the dynamic flight simulator of a quadrotor. Results show high precision and robustness of the attitude estimation algorithm, with a reduced computational cost, being ready to be implemented on low-cost platforms.

Low-Cost Commercial Lego™ Platform for Mobile Robotics

2010 ◽  
Vol 47 (2) ◽  
pp. 132-150 ◽  
Author(s):  
Erik Cuevas ◽  
Daniel Zaldivar ◽  
Marco Pérez-Cisneros
Keyword(s):  
Higher Education ◽  
Mobile Robotics ◽  
Position Control ◽  
Low Cost ◽  
Complex Problem ◽  
Control Algorithms ◽  
Robotic Platform ◽  
Automatic Control Theory ◽  
Key Issues ◽  
Set Up

This paper shows the potential of a Lego™-based low-cost commercial robotic platform for learning and testing prototypes in higher education and research. The overall set-up aims to explain mobile robotic issues, including mechatronics, robotics and automatic control theory. The capabilities and limitations of Lego robots are studied within two experiments: the first shows how to eliminate a number of restrictions in Lego robots using some programming alternatives; the second addresses the complex problem of multi-position control. Algorithms and their additional tools have been fully designed, applied and documented, and the results are shown throughout the paper. The platform was found to be suitable for teaching and researching key issues related to the aforementioned fields.

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