Local Navigation Research Articles

Intelligent Fault Diagnosis Methods for Hydraulic Piston Pumps: A Review

As the modern industry rapidly advances toward digitalization, networking, and intelligence, intelligent fault diagnosis technology has become a necessary measure to ensure the safe and stable operation of mechanical equipment and effectively avoid major disaster accidents and huge economic losses caused by mechanical equipment failure. As the “power heart” of hydraulic transmission systems, hydraulic piston pumps (HPPs) occupy an important position in aerospace, navigation, national defense, industry, and many other high-tech fields due to their high-rated pressure, compact structure, high efficiency, convenient flow regulation, and other advantages. Faults in HPPs can create serious hazards. In this paper, the research on fault recognition technology for HPPs is reviewed. Firstly, the existing fault diagnosis methods are described, and the typical fault types and mechanisms of HPPs are introduced. Then, the current research achievements regarding fault diagnosis in HPPs are summarized based on three aspects: the traditional intelligent fault diagnosis method, the modern intelligent fault diagnosis method, and the combined intelligent fault diagnosis method. Finally, the future development trend of fault identification methods for HPPs is discussed and summarized. This work provides a reference for developing intelligent, efficient, and accurate fault recognition methods for HPPs. Moreover, this review will help to increase the safety, stability, and reliability of HPPs and promote the implementation of hydraulic transmission technology in the era of intelligent operation and maintenance.

A Depth-Based Hybrid Approach for Safe Flight Corridor Generation in Memoryless Planning.

This paper presents a depth-based hybrid method to generate safe flight corridors for a memoryless local navigation planner. It is first proposed to use raw depth images as inputs in the learning-based object-detection engine with no requirement for map fusion. We then employ an object-detection network to directly predict the base of polyhedral safe corridors in a new raw depth image. Furthermore, we apply a verification procedure to eliminate any false predictions so that the resulting collision-free corridors are guaranteed. More importantly, the proposed mechanism helps produce separate safe corridors with minimal overlap that are suitable to be used as space boundaries for path planning. The average intersection of union (IoU) of corridors obtained by the proposed algorithm is less than 2%. To evaluate the effectiveness of our method, we incorporated it into a memoryless planner with a straight-line path-planning algorithm. We then tested the entire system in both synthetic and real-world obstacle-dense environments. The obtained results with very high success rates demonstrate that the proposed approach is highly capable of producing safe corridors for memoryless local planning.

Cross-Modal Images Matching Based Enhancement to MEMS INS for UAV Navigation in GNSS Denied Environments

A new cross-modal image matching method is proposed to solve the problem that unmanned aerial vehicles (UAVs) are difficult to navigate in GPS-free environment and night environment. In this algorithm, infrared image or visible image is matched with satellite visible image. The matching process is divided into two steps, namely, coarse matching and fine alignment. Based on the dense structure features, the coarse matching algorithm can realize the position update above 10 Hz with a small amount of computation. Based on the end-to-end matching network, the fine alignment algorithm can align the multi-sensor image with the satellite image under the condition of interference. In order to obtain the position and heading information with higher accuracy, the fusion of the information after visual matching with the inertial information can restrain the divergence of the inertial navigation position error. The experiment shows that it has the advantages of strong anti-interference ability, strong reliability, and low requirements on hardware, which is expected to be applied in the field of unmanned navigation.

Indoor and Outdoor Fusion Positioning Technology Based on BeiDou Satellite Navigation

In order to solve the inaccuracy and discontinuity of BeiDou differential indoor and outdoor navigation and positioning, this article highlights an indoor and outdoor fusion positioning method based on BeiDou differential and WIFI. This positioning method combines the micro-inertial navigation positioning technology with a single positioning method such as Bluetooth, WIFI fingerprint, ZigBee, ultra-wideband UWB, etc., to correct the BeiDou pseudo range equation to reduce the spatial pseudo range error. And it can integrate BeiDou differential pseudo range equation and linear filtering algorithm to achieve precise positioning of navigation. The research results show that the method realizes the positioning of the indoor and outdoor interactive area by fusing the satellite pseudo-range equation and the base station pseudo-range equation. And it realizes the seamless integration of indoor and outdoor precise positioning, which improves the positioning accuracy and reliability.

Ensuring situational awareness of the moving objects group using one reference navigation station

Problem statement. In the conditions of radio suppression of the global navigation satellite systems, situational awareness of a group of moving objects can be provided using local navigation. Known methods based on the use of local navigation to ensure situational awareness require the mutual exchange of information between the objects of the group, and used several reference stations to determine the coordinates. Purpose. To develop and research of a method of mutual awareness of each moving object about the spatio-temporal state of all moving objects of the group without organizing additional information exchange between the objects of the group, based on the use of one reference navigation station with known local coordinates. Results. A method for ensuring situational awareness of a group of moving objects is proposed. Method based on the use of one reference navigation station equipped with a radio direction finder. The method ensures positioning accuracy of the follower object on board the lead object up to 10 m when the follower object is within the interfocal space of the goniometric-difference-range-measuring system formed by the reference navigation station and the lead object. When the follower object leaves the interfocal space degradation of the accuracy characteristics up to 100 m is observed, which is associated with an increase in the values of the geometric factor. In this case, the accuracy of estimating the delay of interrogation and response signals should be no worse than 5×10-7 s, and the measurement error of the azimuth angle in the radio direction finder of the reference navigation station should not exceed 3-5°. Practical significance. The proposed method can be used in practice to ensure situational awareness of a group of subscribers of a local communication system for special purposes.

Structural models based on spectral graph theory for land-based digital communication networks

Problem statement. For the organization of digital communication networks in the range of meter and decimeter waves, as well as when providing communications based on them in hard-to-reach areas, problems arise related to maintaining the stability and continuity of information exchange between the switching nodes of the ground infrastructure. The existing approaches to solving these problems are based on the use of means of retransmission using radio relay stations and individual flight-lifting equipment. However, with limited deployment time, in emergency situations and when performing special tasks, these approaches are unacceptable for a number of objective reasons. Therefore, the search for ways to improve digital communication networks in the range of meter and decimeter waves is relevant and has important scientific and practical significance for ensuring the stability and continuity of information exchange by ground switching nodes in a given area. Purpose. To develop a structurally stable model of digital communication networks in the range of meter and decimeter waves based on a group of unmanned aerial vehicles, ensuring the organization of continuous information exchange of ground switching nodes in a given area for the required period of time. Results. Based on the results of the research, practical recommendations are formulated for their use to solve the problems of organization, restoration and redundancy, as well as the operational build-up of digital communication networks in the range of meter and decimeter waves for a given time interval in unfavorable operating conditions. The prospects for further research in the organization of the structural contour of the complex multi-circuit adaptation of digital communication networks for various purposes are determined. Practical significance. The results can be used by specialists in the field of satellite radio navigation in the development of local navigation systems.

Radio transmitting device of local navigation systems with adaptive adjustment of radio signal spectrum parameters

Problem statement. Existing radio transmitting devices use a non-tunable baseband filter focused on achieving a minimum level of out-of-band radio signal radiation, which leads to a decrease in the efficiency of using the energy resource of the radio transmitting device caused by an increase in the peak factor. Purpose. improving the efficiency of using the energy resource of the radio transmitting device is adaptive dynamic control of the parameters of the spectrum of the radiated radio signal of the radio transmitting device, depending on the results of monitoring the electromagnetic environment. Results. The proposed technical solution will make it possible to increase the efficiency of using the energy resource of the radio transmitting device by adaptive dynamic control of the parameters of the spectrum of the emitted signal, depending on the results of monitoring electromagnetic compatibility in the radio frequency bands of out-of-band radiation of the radio transmitting device. Practical significance. The results can be used by specialists in the field of radio communications and radio navigation in the development of radio transmitting devices with a reduced level of out-of-band radiation.

Space Relative Position and Attitude Measurement Method Based on Solid State Lidar and High Precision Cooperative Target

With the continuous advancement and upgrading of human space exploration, the complexity and difficulty of space missions are increasing. Space manipulation, rendezvous and docking, and situation awareness of non cooperative targets have become important components of space missions. Relative position and attitude navigation system is an important part of space rendezvous and docking and space manipulation system. At present, the method of matching with cooperative target is mainly used for high-precision relative position and attitude measurement.This paper introduces a method of matching solid-state lidar with high-precision cooperative target for attitude determination. First, a design method of three-dimensional cooperative target is carried out, and then a mathematical model of target recognition is constructed. Three criteria for recognition and matching are proposed. In the third part of the article, the specific process of this method is introduced, and experimental verification is carried out. The experiment shows that the method can achieve the position measurement accuracy of 0.006m and the attitude measurement accuracy of 0.15 ° , and has important application value in various high-precision space missions.

Perancangan Sistem Keamanan Tambahan Pada Kendaraan Menggunakan Tracker SMS

Motor vehicle theft continues to pose a significant issue, primarily due to the vulnerability of security systems relying on manual keys. Thieves are well-versed in exploiting this weakness, necessitating innovative solutions. This study's objective is to design a tool that employs a GPS tracker and SMS to provide precise location coordinates. Additionally, it aims to deter motor vehicle theft by interrupting the electric current flow in the vehicle. Using the Research and Development (R&D) method based on prior research, the outcome is a system capable of providing location points at extensive distances beyond conventional vehicle boundaries. In summary, this device interacts by sending pre-programmed commands to Arduino Uno, with ON functioning to activate electrical systems, OFF for deactivation, and LOCATION for requesting navigational position messages.

Research on Path Tracking for an Orchard Mowing Robot Based on Cascaded Model Predictive Control and Anti-Slip Drive Control

In complex orchard environments, orchard mowing robots are prone to longitudinal slippage because of the characteristics of tires and the adhesion conditions of the road surface, which makes it difficult for the robots to maintain high-precision path tracking and autonomous navigation positioning. This not only affects the accuracy of path tracking but also leads to unstable motion for the mowing robots. To solve the above problems, we take an orchard mowing robot as the control object and establish a cascaded path-tracking controller and an adaptive time domain model based on a kinematics model. By designing a linear error model, an objective function, and constraint conditions for the mowing robot, the optimal linear velocity and angular velocity of the mower are obtained and converted into the speed of the driving wheel. Then, an anti-slip driving controller is designed based on fuzzy control of the slip rate. The slip-rate-based fuzzy controller is constructed according to the real-time speed of the mower and the reference speed of the driving wheel solved by the model predictive controller, and anti-slip driving control is implemented through a combination of a PID controller and a tire dynamics model. To verify the effectiveness of the proposed method, simulation and field experiments are conducted. The experimental results show that the slip rate of the driving wheel of the mower remains within the target slip rate range in the orchard working environment, avoiding excessive driving wheel sliding. Furthermore, the average lateral error of the path-tracking controller is controlled within 0.05 m, and the average value of the longitudinal error is kept within 0.04 m, which satisfies the control accuracy requirements of lawn mower operations. The proposed method provides a reference optimization scheme for improving the path-tracking and motion stability of a mowing robot.

Investigation of Obstacle Prediction Network for Improving Home-Care Robot Navigation Performance

Home-care manipulation robot requires exploring and performing the navigation task safely to reach the grasping target and ensure human safety in the home environment. An indoor home environment has complex obstacles such as chairs, tables, and sports equipment, which make it difficult for robots that rely on 2D laser rangefinders to detect. On the other hand, the conventional approaches overcome the problem by using 3D LiDAR, RGB-D camera, or fusing sensor data. The convolutional neural network has shown promising results in dealing with unseen obstacles in navigation by predicting the unseen obstacle from 2D grid maps to perform collision avoidance using 2D laser rangefinders only. Thus, this paper investigated the predicted grid map from the obstacle prediction network result for improving indoor navigation performance using only 2D LiDAR measurement. This work was evaluated by combining the configuration of the various local planners, type of static obstacles, raw map, and predicted map. Our investigation demonstrated that using the predicted grid map enabled all the local planners to achieve a better collision-free path by using the 2D laser rangefinders only rather than the RGB-D camera with 2D laser rangefinders with a raw map. This advanced investigation considers that the predicted map is potentially helpful for future work in the learning-based local navigation system.

Robot indoor navigation point cloud map generation algorithm based on visual sensing

Abstract At present, low-cost Red Green Blue Depth (RGB-D) sensors are mainly used in indoor robot environment perception, but the depth information obtained by RGB-D cameras has problems such as poor accuracy and high noise, and the generated 3D color point cloud map has low accuracy. In order to solve these problems, this article proposes a vision sensor-based point cloud map generation algorithm for robot indoor navigation. The aim is to obtain a more accurate point cloud map through visual SLAM and Kalman filtering visual-inertial navigation attitude fusion algorithm. The results show that in the positioning speed test data of the fusion algorithm in this study, the average time-consuming of camera tracking is 23.4 ms, which can meet the processing speed requirement of 42 frames per second. The yaw angle error of the fusion algorithm is the smallest, and the ATE test values of the algorithm are smaller than those of the Inertial measurement unit and Simultaneous-Localization-and-Mapping algorithms. This research algorithm can make the mapping process more stable and robust. It can use visual sensors to make more accurate route planning, and this algorithm improves the indoor positioning accuracy of the robot. In addition, the research algorithm can also obtain a dense point cloud map in real time, which provides a more comprehensive idea for the research of robot indoor navigation point cloud map generation.

A hybrid observer for localization from noisy inertial data and sporadic position measurements

We propose an asymptotic position and speed observer for inertial navigation in the case where the position measurements are sporadic and affected by noise. We cast the problem in a hybrid dynamics framework where the continuous motion is affected by unknown continuous-time disturbances and the sporadic position measurements are affected by discrete-time noise. We show that the peculiar hybrid cascaded structure describing the estimation error dynamics is globally finite-gain exponentially ISS with gains depending intuitively on our tuning parameters. Experimental results, as well as the comparison with an Extended Kalman Filter (EKF), confirm the effectiveness of the proposed solution with an execution time two orders of magnitude faster and with a simplified observer tuning because our bounds are an explicit function of the observer tuning knobs.

Barometer assisted smartphone localization for vehicle navigation in multilayer road networks

Multilayer transport structures, such as elevated roads and tunnels, are increasingly used to solve the growing traffic congestion problems in dense urban areas. It presents a challenge for navigation systems to determine which layer the vehicle is running on when elevated roads or tunnels are parallel to and close to surface roads. In this paper, we propose a smartphone-based positioning method to provide accurate position and road layer for vehicle navigation in multilayer road networks. Systemic errors of barometers are calibrated with GNSS measurements, local Digital Surface Model (DSM), and Mean Sea Level pressure. Then, barometer output absolute altitudes are integrated with GNSS and IMU to achieve 3D vehicle positioning. Using absolute altitudes, DSM, and GNSS information, the road layer can be identified without initial layer information in multilayer road networks. Experiment results demonstrate that the proposed method can provide accurate location and road layer in multilayer road networks.

Pedestrians in static crowds are not grains, but game players.

The local navigation of pedestrians is assumed to involve no anticipation beyond the most imminent collisions, in most models. These typically fail to reproduce some key features experimentally evidenced in dense crowds crossed by an intruder, namely, transverse displacements toward regions of higher density due to the anticipation of the intruder's crossing. We introduce a minimal model based on mean-field games, emulating agents planning out a global strategy that minimizes their overall discomfort. By solving the problem in the permanent regime thanks to an elegant analogy with the nonlinear Schrödinger's equation, we are able to identify the two main variables governing the model's behavior and to exhaustively investigate its phase diagram. We find that, compared to some prominent microscopic approaches, the model is remarkably successful in replicating the experimental observations associated with the intruder experiment. In addition, the model can capture other daily-life situations such as partial metro boarding.

AdaptiveON: Adaptive Outdoor Local Navigation Method for Stable and Reliable Actions

We present a novel outdoor navigation algorithm to generate stable and efficient actions to navigate a robot to reach a goal. We use a multi-stage training pipeline and show that our approach produces policies that result in stable and reliable robot navigation on complex terrains. Based on the Proximal Policy Optimization (PPO) algorithm, we developed a novel method to achieve multiple capabilities for outdoor local navigation tasks, namely alleviating the robot's drifting, keeping the robot stable on bumpy terrains, avoiding climbing on hills with steep elevation changes, and avoiding collisions. Our training process mitigates the reality (sim-to-real) gap by introducing generalized environmental and robotic parameters and training with rich features captured from light detection and ranging (Lidar) sensor in a high-fidelity Unity simulator. We evaluate our method in both simulation and real-world environments using Clearpath Husky and Jackal robots. Further, we compare our method against the state-of-the-art approaches and observe that, in the real world, our method improves stability by at least 30.7% on uneven terrains, reduces drifting by 8.08%, and decreases the elevation changes by 14.75%.

Method of spatial cross-coupling elimination of control system channels for object guidance using two TDoA measurements

The problem of object guidance to the target point using two time difference of arrival (TDoA) measurements obtained from three navigation positions is considered. A general equation that describes a kinematic trajectory of the object along the line of intersection of two object position hyperboloids corresponding to the two TDoA measurements is obtained. It has been found out that the kinematic trajectory of the object lies in a plane perpendicular to the plane of three navigation positions. This kinematic trajectory can be described by the conic equation in the general case, and in the range of position parameters used in practice this equation yields a hyperbola. A method of elimination of object spatial cross-coupled link between control system channels, consisting in a special projection of accelerations of the object during their transformation from the measuring coordinate system to the wind coordinate system is described. This made it possible to implement object control in TDoA navigation system with three navigation positions only using two identical expressions of the kinematic link obtained for a planar case without full spatial equation for kinematic link of the object’s motion and TDoA information. A computer simulation of the object guidance to a target point in space using two TDoA measurements was performed to check the accordance of the acceleration design expressions, which produced a positive results of viewed method. The approach described in the article makes it possible to implement object guidance using TDoA navigation system if available only three of four required navigation positions.

Initial Positioning of Terrain Relative Navigation Under Pseudo-Peaks Interference

Initial Positioning of Terrain Relative Navigation Under Pseudo-Peaks Interference

Phased Array Radio Navigation System on UAVs: Real-Time Implementation of In-flight Calibration⋆

Unmanned aerial vehicles (UAV) require an alternative positioning system to the global navigation satellite systems (GNSS) for safety-critical operations since GNSS is prone to unintentional or malicious electromagnetic interference. As a possible redundant positioning solution independent of GNSS, the phased array radio system (PARS) has proved its potential as a local navigation system for UAVs. Previous work suggested an automatic calibration algorithm to estimate the precise PARS ground antenna orientation to improve PARS positioning accuracy. This algorithm was then integrated with PARS- and barometer-aided inertial navigation system (INS) based on multiplicative extended Kalman filter (MEKF) to enable in-flight calibration when GNSS is available. This paper presents the implementation of the previously suggested aided-INS with in-flight calibration mode for real-time operation.

Traversability Aware graph-based Subterranean Exploration with Unmanned Aerial Vehicles*

Subterranean exploration and mapping for search and rescue robotics have become an emerging research direction since the DARPA organized Subterranean Challenge. As part of development efforts within the team CoSTAR (Collaborative SubTerranean Autonomous Robots) in the Sub-T challenge, this work establishes a novel traversable graph-based exploration strategy that utilizes frontiers for local navigation and a fast collision risk-aware graph building for global navigation. The exploration strategy extracts frontiers in an unknown area that contribute to safe navigation while maximizing information gain for the robot. The exploration problem is further bifurcated into local and global exploration for faster decision-making at junctions with the goal of rapidly exploring the area. The local exploration guarantees collision-free straight-line paths to informative frontiers for rapid forward navigation, while global re-positioning utilizes a traversable graph subject to geometrical collision checks within the occupancy map. The pathfinding in a graph is addressed using a heuristic, which combines risk margins and travel costs to assist in short yet safe paths to the global frontier in case of a dead end in local exploration. The presented exploration strategy is developed with the goal of making exploration algorithms platform agnostic in order to be able to use it with aerial, as well as ground robots. The proposed method is also evaluated against different state-of-the-art exploration planners in simulated fixed-time budget-based exploration missions on an Unmanned Aerial Vehicle (UAV) in order to benchmark the capabilities and highlight the novelty.