Search results

The motivation to perform research on feedback control system for unmanned aerial vehicles, a fact that each quadrocopter is unstable.

For this reason, it is necessary to design a control system which is capable of making unmanned aerial vehicle vertical take-off and landing (UAV VTOL) stable and controllable. For this purpose, it was decided to use a feedback control system with cascaded PID controller. The main reason for using it was that PID controllers are simple to implement and do not use much hardware resources. Moreover, cascaded control systems allow to control object response using more parameters than in a standard PID control. STM32 microcontrollers were used to make a real control system. The rapid prototyping using Embedded Coder Toolbox, FreeRTOS and STM32 CubeMX was conducted to design the algorithm of the feedback control system with cascaded PID controller for unmanned aerial vehicle vertical take-off and landings (UAV VTOLs).

During research, an algorithm of UAV VTOL control using the feedback control system with cascaded PID controller was designed. Tests were performed for the designed algorithm in the model simulation in Matlab/Simulink and in the real conditions.

It has been proved that an additional control loop must have a full PID controller. Moreover, a new library is presented for STM32 microcontrollers made using the Embedded Coder Toolbox just for the research. This library enabled to use rapid prototyping while developing the control algorithms.

Unmanned vehicles flight is controlled by embedded circuits in the aircraft, under the remote control of a pilot on the ground. This circuit, called autopilot, represents one of the key elements inside the vehicles. The authors developed one of the smallest autopilot, specifically designed for low-weight low-power applications. The paper aims to discuss these issues.

The system is based on STM32 ARM Cortex M3 microcontroller. It includes an onboard 9 DOF IMU (MPU9150) and a 2.4 GHz wireless transceiver (nRF24L01+).

The embedded lightweight kinematic autopilot (ELKA) can pilot up to eight servomotors, and can be used to monitor more than 100 sensors. The final assembled board is 28×21 mm2 and weighs around 1.2 grams (battery excluded), and has successfully passed initial functionality tests.

The authors presented the design, fabrication and initial tests of a lightweight kinematic autopilot (ELKA board version 1.0). The system has been designed in order to upgrade the state-of-art capability in sensing and processing over a previous autopilot (GINA), which is of similar weight and size. The small size (28×21 mm2) and the lightweight (around 1.2 grams) make ELKA one of the smallest autopilot in the world.

Deployment of deep neural networks on embedded devices is becoming increasingly popular because it can reduce latency and energy consumption for data communication. This paper aims to give out a method for deployment the deep neural networks on a quad-rotor aircraft for further expanding its application scope.

In this paper, a design scheme is proposed to implement the flight mission of the quad-rotor aircraft based on multi-sensor fusion. It integrates attitude acquisition module, global positioning system position acquisition module, optical flow sensor, ultrasonic sensor and Bluetooth communication module, etc. A 32-bit microcontroller is adopted as the main controller for the quad-rotor aircraft. To make the quad-rotor aircraft be more intelligent, the study also proposes a method to deploy the pre-trained deep neural networks model on the microcontroller based on the software packages of the RT-Thread internet of things operating system.

This design provides a simple and efficient design scheme to further integrate artificial intelligence (AI) algorithm for the control system design of quad-rotor aircraft.

This method provides an application example and a design reference for the implementation of AI algorithms on unmanned aerial vehicle or terminal robots.

Utilizing electrical discharge machining (EDM) to process micro-holes in superalloys may lead to the formation of remelting layers and micro-cracks on the machined surface. This work proposes a method of composite processing of EDM and ultrasonic vibration drilling for machining precision micro-holes in complex positions of superalloys.

A six-axis computer numerical control (CNC) machine tool was developed, whose software control system adopted a real-time control architecture that integrates electrical discharge and ultrasonic vibration drilling. Among them, the CNC system software was developed based on Windows + RTX architecture, which could process the real-time processing state received by the hardware terminal and adjust the processing state. Based on the SoC (System on Chip) technology, an architecture for a pulse generator was developed. The circuit of the pulse generator was designed and implemented. Additionally, a composite mechanical system was engineered for both drilling and EDM. Two sets of control boards were designed for the hardware terminal. One set was the EDM discharge control board, which detected the discharge state and provided the pulse waveform for turning on the transistor. The other was a relay control card based on STM32, which could meet the switch between EDM and ultrasonic vibration, and used the Modbus protocol to communicate with the machining control software.

The mechanical structure of the designed composite machine tool can effectively avoid interference between the EDM spindle and the drilling spindle. The removal rate of the remelting layer on 1.5 mm single crystal superalloys after composite processing can reach over 90%. The average processing time per millimeter was 55 s, and the measured inner surface roughness of the hole was less than 1.6 µm, which realized the  micro-hole machining without remelting layer, heat affected zone and micro-cracks in the single crystal superalloy.

The test results proved that the key techniques developed in this paper were suite for micro-hole machining of special materials.

To make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no longer satisfied with enabling robots to build maps by remote control, more needs will focus on the autonomous exploration of unknown areas, which refer to the low light, complex spatial features and a series of unstructured environment, lick underground special space (dark and multiintersection). This study aims to propose a novel robot structure with mapping and autonomous exploration algorithms. The experiment proves the detection ability of the robot.

A small bio-inspired mobile robot suitable for underground special space (dark and multiintersection) is designed, and the control system is set up based on STM32 and Jetson Nano. The robot is equipped with double laser sensor and Ackerman chassis structure, which can adapt to the practical requirements of exploration in underground special space. Based on the graph optimization SLAM method, an optimization method for map construction is proposed. The Iterative Closest Point (ICP) algorithm is used to match two frames of laser to recalculate the relative pose of the robot, which improves the sensor utilization rate of the robot in underground space and also increase the synchronous positioning accuracy. Moreover, based on boundary cells and rapidly-exploring random tree (RRT) algorithm, a new Bio-RRT method for robot autonomous exploration is proposed in addition.

According to the experimental results, it can be seen that the upgraded SLAM method proposed in this paper achieves better results in map construction. At the same time, the algorithm presents good real-time performance as well as high accuracy and strong maintainability, particularly it can update the map continuously with the passing of time and ensure the positioning accuracy in the process of map updating. The Bio-RRT method fused with the firing excitation mechanism of boundary cells has a more purposeful random tree growth. The number of random tree expansion nodes is less, and the amount of information to be processed is reduced, which leads to the path planning time shorter and the efficiency higher. In addition, the target bias makes the random tree grow directly toward the target point with a certain probability, and the obtained path nodes are basically distributed on or on both sides of the line between the initial point and the target point, which makes the path length shorter and reduces the moving cost of the mobile robot. The final experimental results demonstrate that the proposed upgraded SLAM and Bio-RRT methods can better complete the underground special space exploration task.

Based on the background of robot autonomous exploration in underground special space, a new bio-inspired mobile robot structure with mapping and autonomous exploration algorithm is proposed in this paper. The robot structure is constructed, and the perceptual unit, control unit, driving unit and communication unit are described in detail. The robot can satisfy the practical requirements of exploring the underground dark and multiintersection space. Then, the upgraded graph optimization laser SLAM algorithm and interframe matching optimization method are proposed in this paper. The Bio-RRT independent exploration method is finally proposed, which takes shorter time in equally open space and the search strategy for multiintersection space is more efficient. The experimental results demonstrate that the proposed upgrade SLAM and Bio-RRT methods can better complete the underground space exploration task.

The specific modulation methods are used to control different kind of single-phase, as well as three-phase, inverters to ensure flexibility and high quality of the output waveform. This paper aims to present a combination of two classical methods, namely, pulse width modulation method and direct digital synthesis modulation method.

The total harmonic distortion of output waveforms of single-phase inverter based on elaborated modulation method has been determined by means of fast Fourier transform analysis. Tests have been carried out by using standard low-frequency application and also a wireless resonant energy link system.

Applying appropriate timer parameters of microcontroller enables to obtain a waveform for given output parameters (amplitude, frequency, frequency modulation index, etc.). The only limitation is the computing power of a microcontroller.

The elaborated method can be successfully used in both low- and high-frequency application ensuring high level of output waveform quality. Additional signal generators and the control of amplitude modulation ratio are no longer indispensable, what simplify immensely a control system.

The purpose of this study is to design a wearable medical device as a human care platform and to introduce the design details, key technologies and practical implementation methods of the system.

A multi-channel data acquisition scheme based on PCI-E (rapid interconnection of peripheral components) was proposed. The flexible biosensor is integrated with the flexible data acquisition card with monitoring capability, and the embedded (device that can operate independently) chip STM32F103VET6 is used to realize the simultaneous processing of multi-channel human health parameters. The human health parameters were transferred to the upper computer LabVIEW by intelligent clothing through USB or wireless Bluetooth to complete the transmission and processing of clinical data, which facilitates the analysis of medical data.

The smart clothing provides a mobile medical cloud platform for wearable medical through cloud computing, which can continuously monitor the body's wrist movement, body temperature and perspiration for 24 h. The result shows that each channel is completely accurate to the top computer display, which can meet the expected requirements, and the wearable instant care system can be applied to healthcare.

The smart clothing in this study is based on the monitoring and diagnosis of textiles, and the electronic communication devices can cooperate and interact to form a wearable textile system that provides medical monitoring and prevention services to individuals in the fastest and most accurate way. Each channel of the system is precisely matched to the display screen of the host computer and meets the expected requirements. As a real-time human health protection platform technology, continuous monitoring of human vital signs can complete the application of human motion detection, medical health monitoring and human–computer interaction. Ultimately, such an intelligent garment will become an integral part of our everyday clothing.

The widespread use of drones among the general public has led to an alarming increase in accidents, some with lethal consequences. As drone blades are made from rigid materials and rotate at very high speeds, their impact with a human body can result in fatal injuries. Reliable collision detection combined with near-instantaneous braking of the drone’s rotor(s) can substantially lessen the severity of injuries sustained. The purpose of this paper is to achieve a safety solution which can be easily integrated into new products, or retrofitted into existing systems.

Through a proof of concept, this paper demonstrates the possibility of detecting a collision with a drone propeller absent any hardware modifications to the drone’s instrumentation. The solution relies on current-sensor readings, ordinarily used for monitoring the battery status of electrically actuated drones. The braking is achieved purely by reconfiguring the motor’s control strategy, without the need for additional hardware, as has been the case in previous works.

This paper demonstrates the possibility of detecting a collision with a drone propeller absent any hardware modifications to the drone’s instrumentation.

Compared to previous works which require installing additional hardware, the solution is purely software. This makes it very easy to integrate into existing systems or new products, at no additional cost. In experiments conducted on a prototype system, the solution was shown capable of detecting a collision and braking the motor in fewer than 20 ms. This allowed attenuating centimetre-deep cuts made to a piece of meat by an unprotected rotor to mere superficial scratches.

Regular cable trench inspection is crucial, and robotics automation provides an efficient and safer alternative to manual labor. However, existing robots have limited capabilities in traversing obstacles and lack a mechanical arm for detecting cables and equipment. This study aims to develop an intelligent robot for cable trench inspection, enhancing obstacle-crossing abilities and incorporating a mechanical arm for inspection tasks.

This study presents an intelligent robot for cable trench inspection, featuring a six-degree-of-freedom mechanical arm mounted on a six-track chassis with four flippers. The robot's climbing and obstacle-crossing stability, as well as the motion range of the mechanical arm, are analyzed. The positioning, navigation and remote monitoring systems are developed. Experiments, including climbing and obstacle-crossing performance tests, along with navigation and positioning system tests, are conducted. Finally, the robot's practicability is verified through field testing.

Equipped with flipper tracks, the cable trench inspection robot can traverse obstacles up to 30 cm high and maintain stable locomotion on 30° slopes. Its navigation system enables autonomous operation, while the mechanical arm performs cable current detection tasks. The remote monitoring system provides comprehensive control of the robot and environmental parameter monitoring in cable trenches.

The front and rear flipper tracks enhance the robot's ability to traverse obstacles in cable trenches. The mechanical arm addresses cable current and equipment contact detection issues. The navigation and remote monitoring systems improve the robot's autonomous operation and environmental monitoring capabilities. Implementing this robot can advance the automation and intelligence of cable trench inspections.