On-board Computer Research Articles

Robust Launch Vehicle Trajectory Optimization with Stage Impact and Heat Flux Constraints

A fast trajectory optimization/guidance algorithm in the presence of path constraints for a multistage launch vehicle is presented in this work. The optimization problem is to maximize the payload to be injected into a geostationary transfer orbit with constraints on argument of perigee, second-stage impact point longitude, and heat flux constraint on the third stage that flies a low-altitude trajectory. These constraints constitute a unique set of equality and inequality constraints as they are contradictory in nature. Most of the gradient-based trajectory optimization schemes require an initial guess close enough to the optimal value for assured convergence. In addition, the rate of convergence deteriorates in the presence of inequality constraints. These issues are addressed by providing a solution to the optimization problem with low sensitivity to the initial guess profiles. A self-starting optimization scheme that can generate initial guess profiles automatically from boundary conditions is the major contribution of this work. The proposed method presented in this paper also gives a methodology for real-time implementation of the optimization scheme in the onboard computer. The sensitivity to initial guess in a gradient-based optimization procedure, in the presence of inequality constraints, is clearly brought out as part of this work by studying the convergence from random sets of initial guess profiles. The real-time implementation of the algorithm is validated with various initial conditions in deterministic as well as Monte Carlo sense to establish the robustness of the algorithm.

Guidance for autonomous spacecraft repointing under attitude constraints and actuator limitations

Current and future space observation missions need to perform many large-angle, multi-axis slew maneuvers between observations while keeping the scientific instrument’s attitude in a safe region. The state-of-practice typically divides each multi-axis maneuver into a series of single-axis sub-maneuvers, each of which is computed by restricting its guidance solution to the exact spacecraft momentum capacity. This ensures that the constraints are explicitly considered and results in a simple on-board implementation of the guidance algorithm, but is time-consuming and non-optimal for the whole multi-axis maneuver. Addressing this issue, this article presents a novel analytical guidance approach that relies on the convexity of the permissible attitude zone. The proposed guidance is time-optimal for a given spacecraft design and set of admissible observation targets. Both guidance approaches are compared using a multi-body/multi-actuator benchmark spacecraft, whose complex repointing phase requires an autonomous on-board guidance computation. It is shown that the proposed approach is systematic and that the reduction in maneuver time, compared to the state-of-practice approach, is considerable.

Online time-varying navigation ratio identification and state estimation of cooperative attack

An online navigation ratio identification model based on the gated recurrent unit (GRU) and a state estimation extended Kalman filter (EKF) are proposed under the scenario in which multiple enemy missiles attack a stationary target using a time-cooperative guidance law. The navigation ratio identification is solved as a dynamic problem, and the time-varying navigation ratios of each missile, instead of the effective navigation constants and cooperative gains, are identified in this paper. In other words, the simplified assumption that the true value is within a known finite set, which is generally adopted in a conventional identification-estimation scheme such as multiple-model adaptive estimators (MMAEs) or interacting multiple-models (IMMs), is discarded. To increase the training speed and identification accuracy, the improved multiple-model mechanism (IMMM) is adopted, and a multiple-model layer, in which regimes representing different values are set, is connected behind a conventional neural network. Since the navigation ratios are identified online, the connections between missiles are decoupled, and only one filter is required for each missile. This could greatly reduce the computational burden of onboard computers. The effectiveness of the proposed online identification model and the performance of the state estimation filter are demonstrated through numerical simulations.

A Design Concept of an Intelligent Onboard Computer Network

The article suggests design principles of an advanced onboard computer network with an intelligent control system. It describes the main advantages of designing an onboard computer network based on fibre optics, which allows the implementation of an integrated intellectual system performing intelligent inference in emergency situations. The suggested principles significantly increase the reliability and fault tolerance of avionics suits, which, in turn, enhances flight safety. The suggested concept aims to solve a number of important problems including the design of a switchless computing environment, the development of the methods for dynamic reconfiguration of avionics suits with such an environment, and the implementation of a specialised multilevel intelligent avionics system within this environment.

A new methodology for bare soils detection using extended Bragg covariance matrix forms

ABSTRACT This paper presents a new methodology for detecting bare rough soil in non-urban areas using synthetic aperture radar data. Our approach involves matching the covariance/coherence matrix to the extended Bragg (xBragg) model. Our method uses automatic OTSU’s thresholding based on roughness angles histogram to determine output classes and avoid complex calculations, making it suitable for onboard computing. The procedure is suitable for a range of soil roughness but not for highly specular surfaces. The performance of the suggested methodology was evaluated using simulated data and real L- and P-band SAR datasets from two different sites with various features. Our results demonstrate the effectiveness of the method for rough agricultural and natural surfaces, with good performance and a success rate of up to about across a wide range of roughness values from to .

Distributed Nonlinear Trajectory Optimization for Multi-Robot Motion Planning

This work presents a method for multi-robot coordination based on a novel distributed nonlinear model predictive control (NMPC) formulation for trajectory optimization and its modified version to mitigate the effects of packet losses and delays in the communication among the robots. Our algorithms consider that each robot is equipped with an onboard computation unit to solve a local control problem and communicate with neighboring autonomous robots via a wireless network. The difference between the two proposed methods is in the way the robots exchange information to coordinate. The information exchange can occur in a following: 1) synchronous or 2) asynchronous fashion. By relying on the theory of the nonconvex alternating direction method of multipliers (ADMM), we show that the proposed solutions converge to a (local) solution of the centralized problem. For both algorithms, the communication exchange preserves the safety of the robots; that is, collisions with neighboring autonomous robots are prevented. The proposed approaches can be applied to various multi-robot scenarios and robot models. In this work, we assess our methods, both in simulation and with experiments, for the coordination of a team of autonomous vehicles in the following: 1) an unsupervised intersection crossing and 2) the platooning scenarios.

Collision avoidance by constructing and using a passing area in on-board controller

The object of research is the processes of automatic optimal passing of one's own ship with many dangerous targets, including maneuvering ones, by the method of constructing the area of permissible passing parameters in the on-board computer. According to the European Maritime Safety Agency (EMSA), the largest number of ship accidents in 2014–2019 occurred due to collision (32 %). On modern ships, for observation and passing with targets, ARPA (automatic radar plotting aid) is used, which allows to automate manual operations, and the built-in function «Playing the maneuver» provides the navigator with a convenient graphic interface for solving passing problems. At the same time, ARPA is an automated system that assumes the presence of an operator in the control circuit. The presence of a person in the control circuit is related to the «human factor», which is a prerequisite for the occurrence of various types of accidents, including ship collisions. The most effective means of reducing the influence of the «human factor» on control processes is the introduction of automatic control modules in automated systems. The paper develops a method for the passing module, which allows automatic and optimal passing with many targets, including maneuvering ones. The number of targets for passing is not limited by the method, but is limited only by the capabilities of the ARPA to track the targets. The obtained results are explained by the fact that at each step of the on-board computer, a region of permissible passing parameters is constructed for all purposes, passing parameters that optimize a given optimality criterion are selected from the constructed region, the selected parameters are used as software in the control law. The developed method can be used on ships, subject to integration into the existing automated system of an on-board computer with an open architecture, to increase the capabilities of automatic traffic control, in this case, the possibility of automatic optimal passing with many objectives, including maneuvering.

CONTROLLING THE OPERATION OF THE REMOTE DEVICE USING FLASK PYTHON SERVER

A computer model of controlling an unmanned aerial vehicle (UAV) using remote cloud technologies according to predetermined scenarios from the user’s desktop was studied. For this, an experimental setup was created, which includes an unmanned aerial vehicle of the quadcopter type, a personal computer with the Windows operating system, a Raspberry Pi 3 on-board computer with the Raspbian Linux operating system, a Pi Camera V2 video camera, and a Pixhawk autopilot. Worked out connection sequence between client (web browser user) and server (Raspberry Pi 3 with Flask system) and execution of remote commands using HTTP requests. As a framework, the Flask system was chosen, which is one of the simplest and has comprehensive, small-volume documentation. According to the obtained research results, a model of controlling the UAV from the desktop of the user’s personal computer through the on-board computer without using a standard control panel and operator is proposed. According to the obtained research results, a model of remote control of an unmanned aerial vehicle with an on-board computer of the Raspberry Pi type using remote cloud technologies and a control program according to predetermined scenarios is proposed. At the same time, the user works only with the desktop of a personal computer, and accesses through an external or internal network and a Flask-type server to the on-board computer of the UAV without using a standard control panel and operator. The proposed experimental setup includes an unmanned aerial vehicle of the quadcopter type with a Q450 frame and D2212-920 kv engines, a personal computer with a Windows operating system, a Raspberry Pi 3 on-board computer with a Raspbian Linux operating system. It made it possible to realize the set goal of researching the process of controlling an unmanned aerial vehicle using a Flask-type server. It was found that the full time of passing the HTTP request through the browser window and receiving a response from the server about the successful completion of the task does not exceed one second. In the future, it is planned to work out more complex processes of launching and controlling an unmanned aerial vehicle in flights according to predetermined scenarios, including the performance of a task such as neutralizing unauthorized aerial vehicles, as well as returning one’s own UAV to the place of deployment. The proposed system of remote control with the Flask server can also be useful for receiving an immediate notification when detecting certain sounds from foreign unmanned aerial vehicles, detecting and measuring their flight parameters.

Dynamic Target Tracking of Small UAVs in Unstructured Environment

In this paper, an adaptive multi-rotor UAV system of dynamic target tracking and path planning is proposed for the problems of occlusion, lighting change, and similar target interference in an unstructured environment. A DTE-tracker module is designed, consisting of a detector, tracker, and examiner, and proposes a dynamic target capture mechanism to improve the robustness and continuity of target tracking in complex environments. A DWA local path planning algorithm based on a dynamic target tracking task is proposed to control the yaw of the UAV to accurately locate specific targets in the center of the image, and finally achieve the purpose of stable tracking. A UAV platform was built equipped with an onboard computer, laser sensor, and visual sensor, and a series of target tracking and path planning experiments were carried out to verify the effectiveness of the method and test the performance of the algorithm in a complex jungle environment.

Automatic testbed with a visual motion tracking system for airborne wind energy applications

AbstractThe architecture and a flight test campaign of a small‐scale testbed aimed at aerodynamic and dynamic characterization of airborne wind energy systems are presented. The testbed involves a two‐line rigid‐framed delta kite and an automatic ground station for the lateral control of the kite and reel‐in/reel‐out of the two tethers. The environment, and the states of the kite, the tethers and the actuators are measured by a set of on‐ground and onboard sensors that include, among others, an inertial measurement unit, GNSS receivers, load cells, actuator encoders, a wind station, and a visual motion tracking (VMT) system based on three cameras and an artificial neural network (YOLOv2). The results of a 5‐min flight, including the take‐off, cross‐wind flight, and landing, were used to analyze the capabilities of the testbed. It was shown that the time derivative of the kite course angle exhibits a linear correlation with both the delayed steering input and the delayed differential tether tension, being the dispersion lower for the latter. The intrinsic and extrinsic calibrations proposed for the VMT system led to a good agreement between the estimation of the kite position and course angle provided by the VMT system and the onboard computer. Moreover, although the YOLOv2 algorithm failed in the detection of the kite within around 5% of the images, the simultaneous non‐detection from the three cameras was below 0.1% during the full flight. Such a reliability suggests that a VMT system can be used as a redundant or backup sensor for the GNSS.

ИССЛЕДОВАНИЕ ПОДХОДОВ К УНИФИКАЦИИ БОРТОВЫХ ВЫЧИСЛИТЕЛЬНЫХ КОМПЛЕКСОВ

Research in the field of creating specialized computing systems for robots is conductedin many world scientific centers, including our country. The development of capabilities ofsensor systems, global navigation systems, growth of computing power and improvement ofalgorithms allow creating onboard computing systems with broad intellectual capabilities.An important, but unsolved problem remains the equipping of such computing systems withdomestically produced microprocessors. One of the difficulties hindering the widespreadintegration of domestic hardware is the problem of unification and standardization of thecomponents of the onboard computers. Unification of onboard computer modules would openup new opportunities for developers of robotic systems by reducing the price and simplifyingdevelopment and modernization. This article discusses approaches to the unification andstandardization of elements of onboard computers, describes the experience of the developmentof ANSI/VITA standards in the field of onboard computers, and also provides examplesof computing modules in a unified COM-Express form-factor based on Elbrus microprocessorsfor onboard computers. Experiments were conducted using unified computing modules based on Elbrus-2C3, Elbrus-1C+ and Elbrus-4C microprocessors. Their applicability forcreation of onboard computing complexes is shown. The necessity of developing a domesticstandard for on-board computer housings and form-factors is shown.

Precision Landing Tests of Tethered Multicopter and VTOL UAV on Moving Landing Pad on a Lake.

Autonomous take-off and landing on a moving landing pad are extraordinarily complex and challenging functionalities of modern UAVs, especially if they must be performed in windy environments. The article presents research focused on achieving such functionalities for two kinds of UAVs, i.e., a tethered multicopter and VTOL. Both vehicles are supported by a landing pad navigation station, which communicates with their ROS-based onboard computer. The computer integrates navigational data from the UAV and the landing pad navigational station through the utilization of an extended Kalman filter, which is a typical approach in such applications. The novelty of the presented system is extending navigational data with data from the ultra wide band (UWB) system, and this makes it possible to achieve a landing accuracy of about 1 m. In the research, landing tests were carried out in real conditions on a lake for both UAVs. In the tests, a special mobile landing pad was built and based on a barge. The results show that the expected accuracy of 1 m is indeed achieved, and both UAVs are ready to be tested in real conditions on a ferry.

An Integrated Framework for Autonomous Sensor Placement With Aerial Robots

Aerial manipulators have the unique ability to cover wide-spread areas within a single mission, making them ideal for the transport and placement of sensors required to build an instrumented environment. Recent work in the field has focused on controllers for aerial interaction that account for compliance during contact-based tasks, omitting integration concerns that are critical to an automated solution. Furthermore, state-of-the-art flying base manipulators are often mechanically and computationally complex, reducing their endurance. Within this work, we present an interactive framework for autonomous sensor placement that incorporates both mechanical and software based compliance, optimised for use on a simple coplanar quadrotor. Under appropriate actuation and perception constraints, we detail the development of a control, perception, and motion planning strategy to enable sensor placement that relies solely on onboard computation and sensing, thus presenting a fully contained and accessible sensor placement approach capable of robust interaction with the environment. An extended finite-state machine is developed to facilitate automated mission planning. Extensive flight experiments are performed to validate the effectiveness of each sub-system, as well as the integrated solution. Experiments result in trajectory tracking errors under <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10 \,\mathrm{mm}$</tex-math></inline-formula> as well as onboard mass estimation errors under <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$0.7 $</tex-math></inline-formula> % for sensors of various weights. A statistical analysis of 162 flight experiments shows the proposed framework's ability to autonomously place sensors within <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$10 \,\mathrm{cm}$</tex-math></inline-formula> of the target with a success rate of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$93.8 $</tex-math></inline-formula> % and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$95 $</tex-math></inline-formula> % confidence interval of (89%, 97%), thus confirming the robustness of our approach. <xref ref-type="fn" rid="fn1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">¹</xref>

An Efficient Egocentric Regulator for Continuous Targeting Problems of the Underactuated Quadrotor

Currently, for the continuous targeting problem with the underactuated quadrotor, a nonlinear optimal control method with high computational efficiency is still missing. To tackle this problem, a novel efficient egocentric regulation approach with high computational efficiency is proposed in this article. Specifically, it directly formulates the optimal control problem in an egocentric manner regarding the quadrotor&#x0027;s body coordinates. Meanwhile, the nonlinearities of the system are decoupled through a mapping of the feedback states and control inputs, between the inertial and body coordinates. In this way, it only requires solving a quadratic performance objective with linear constraints and then generates control inputs analytically. Simulations and mimic biological experiments are carried out to verify the effectiveness and computational efficiency. Results demonstrate that the proposed control approach presents the highest and most stable computational efficiency compared with generic optimizers on different platforms. Particularly, on a commonly utilized onboard computer, our method can compute the control action in approximately 0.3&#x00A0;ms, which is on the order of 350 times faster than that of generic optimizers, establishing a control frequency around 3000&#x00A0;Hz.

A Review: Cybersecurity Challenges and their Solutions in Connected and Autonomous Vehicles (CAVs)

Connected and Autonomous Vehicles (CAVs) are a crucial breakthrough in the automotive industry and a magnificent step toward a safe, secure, and intelligent transportation system (ITS). CAVs offer tremendous benefits to our society and environment, such as mitigation of traffic accidents, reduction in traffic congestion, fewer emissions of harmful gases, etc. However, emerging automotive technology also has some serious safety concerns. One of them is cyber security. Conventional vehicles are less prone to cyber-attacks, but CAVs are more susceptible to such events as they communicate with the surrounding infrastructure and other vehicles. To gather data for a better perception of their surroundings, CAVs are outfitted with state-of-the-art sensors and modules like LiDAR, GPS, RADAR, onboard computers, cameras, etc. Hackers, terrorist organizations, and vandals can manipulate this sensor data or may access the primary control by cyber-attack, which may result in enormous fatalities. The automotive industry must put up a rigid framework against cyber invasions to make CAVs a more reliable and secure means of transportation. This paper provides an overview of cybersecurity challenges in CAVs at the module and software levels. The sources of active and passive threats are analyzed. Finally, a feasible solution is recommended to cope with such threats

Remote control of muscle-driven miniature robots with battery-free wireless optoelectronics.

Bioengineering approaches that combine living cellular components with three-dimensional scaffolds to generate motion can be used to develop a new generation of miniature robots. Integrating on-board electronics and remote control in these biological machines will enable various applications across engineering, biology, and medicine. Here, we present hybrid bioelectronic robots equipped with battery-free and microinorganic light-emitting diodes for wireless control and real-time communication. Centimeter-scale walking robots were computationally designed and optimized to host on-board optoelectronics with independent stimulation of multiple optogenetic skeletal muscles, achieving remote command of walking, turning, plowing, and transport functions both at individual and collective levels. This work paves the way toward a class of biohybrid machines able to combine biological actuation and sensing with on-board computing.

Robust and resilient equilibrium routing mechanism for traffic congestion mitigation built upon correlated equilibrium and distributed optimization

With the rapid development of wireless communication, mobile computing, and GPS technologies, drivers’ route decisions nowadays rely more on navigation services, such as Google or Waze. However, these navigation services don't always come with improved traffic conditions. Individual drivers often make independent and selfish route decisions that are not systematically favorable and thus often result in severe congestions. This study aims to alleviate such problems by exploiting the information gaps between individuals and the central planner (CP). Specifically, we develop a correlated equilibrium routing mechanism (CeRM) for the CP, which drives a group of vehicles’ route choices to an equilibrium with a systematically optimal traffic condition while still satisfying individuals’ selfish nature. Participating drivers would only be better off by following the suggested routing guidance than navigating on their best responses to real-time traffic information. The CeRM is modeled as a nonconvex and nonlinear program involving a large-scale of users. A distributed Augmented Lagrangian algorithm (D-AL) is developed to efficiently solve the CeRM to provide online real-time navigation service, taking advantage of the on-board computation resources of individual vehicles. Considering the D-AL relies on the wireless communications between vehicles and the CP, we proved the convergence robustness of the D-AL against random communication failures and derived the convergence rate upper bound as a function of the communication failure probability. It is noticed that the convergence rate of the D-AL degrades dramatically as the communication failure probability increases, which hampers the applicability of implementing the CeRM in practice. To improve the solution algorithm's resilience in the computation performance, we further designed and proved an acceleration scheme aided D-AL (aD-AL) to expedite the convergence rate under the high likelihood of communication failures. Numerical experiments conducted on the Sioux Falls city network confirmed the D-AL's convergence properties, robustness against random communication failures, and the resilience of the aD-AL to solve the CeRM. The experiments also show that the CeRM results in better system performance (have less system cost) compared with the existing Independent Routing (IR) mechanism and user-oriented Equilibrium Routing (uoER) mechanism.

In-Orbit FPGA reprogramming device for small satellites

Development of satellite technologies is a challenging task, which includes design, manufacturing, testing, and in-orbit operation stages. The reliability of each subsystem shall be at the highest level since space has severe environmental conditions and most satellites do not have an opportunity to perform repairment or replacement of their hardware components.In-orbit reprogramming of some devices, such as On-board Computer (OBC), Attitude Control Unit (ACU), and Power Control Unit (PCU) can provide great advantages to a mission by extending the lifetime and performance of a satellite's operation. At the same time, even a small mistake can result in a lot of monetary losses or even failure of a subsystem or the whole project. So, a reprogramming method to be used in space missions shall undergo excessive testing to provide high reliability for updating software in orbit.This paper is devoted to an investigation of available and applicable methods for remote reprogramming of Field-Programmable Gate Array (FPGA) based subsystems.A commercial off-the-shelf (COTS) single board computer (SBC) was used as a standalone subsystem to perform reprogramming of a target device. The SBC was tested extensively and reinforced for ensuring its space-compatibility. Several open-source software-based solutions were considered. Some of them are applicable to a wide range of processor architectures, including ARM. Considered methods could reconfigure an FPGA successfully with some major limitations, which were also described in the paper.Based on the investigation, Xilinx Software Command-line Tool (XSCT) was selected as a reprogramming method for ACU of the latest satellite of iQPS, QPS-SAR-2 (“IZANAMI”).

Design of an Autonomous Cooperative Drone Swarm for Inspections of Safety Critical Infrastructure

Inspection of critical infrastructure with drones is experiencing an increasing uptake in the industry driven by a demand for reduced cost, time, and risk for inspectors. Early deployments of drone inspection services involve manual drone operations with a pilot and do not obtain the technological benefits concerning autonomy, coordination, and cooperation. In this paper, we study the design needed to handle the complexity of an Unmanned Aerial System (UAS) to support autonomous inspection of safety-critical infrastructure. We apply a constructive research approach to link innovation needs with concepts, designs, and validations that include simulation and demonstration of key design parts. Our design approach addresses the complexity of the UAS and provides a selection of technology components for drone and ground control hardware and software including algorithms for autonomous operation and interaction with cloud services. The paper presents a drone perception system with accelerated onboard computing, communication technologies of the UAS, as well as algorithms for swarm membership, formation flying, object detection, and fault detection with artificial intelligence. We find that the design of a cooperative drone swarm and its integration into a custom-built UAS for infrastructure inspection is highly feasible given the current state of the art in electronic components, software, and communication technology.

High-Accuracy and Low-Latency Tracker for UAVs Monitoring Tibetan Antelopes

As the habitat areas of Tibetan antelopes usually exhibit poaching and unpredictable risks, combining target recognition and tracking with intelligent Unmanned Aerial Vehicle (UAV) technology is necessary to obtain the real-time location of injured Tibetan antelopes to better protect and rescue them. (1) Background: The most common way to track an object is to detect each frame of it, and it is not necessary to run the object tracker and classifier at the same rate, because the speed for them to change class is slower than objects move. Especially in the edge reasoning scene, UAV real-time monitoring requires to seek a balance between the frame rate, latency, and accuracy. (2) Methods: A backtracking tracker is proposed to recognize Tibetan antelopes which generates motion vectors through stored optical flow, achieving faster target detection. The lightweight You Only Look Once X (YOLOX) is selected as the baseline model to reduce the dependence on hardware configuration and calculation cost while ensuring detection accuracy. Region-of-Interest (ROI)-to-centroid tracking technology is employed to reduce the processing cost of motion interpolation, and the overall processing frame rate is smoothed by pre-calculating the motions of different objects recognized. The On-Line Object Tracking (OLOT) system with adaptive search area selection is adopted to dynamically adjust the frame rate to reduce energy waste. (3) Results: using YOLOX to trace back in the native Darkenet can reduce latency by 3.75 times, and the latency is only 2.82 ms after about 10 frame hops, with the accuracy being higher than YOLOv3. Compared with traditional algorithms, the proposed algorithm can reduce the tracking latency of UAVs by 50%. By running and comparing in the onboard computer, although the proposed tracker is inferior to KCF in FPS, it is significantly higher than other trackers and is obviously superior to KCF in accuracy. (4) Conclusion: A UAV equipped with the proposed tracker effectively reduces reasoning latency in monitoring Tibetan antelopes, achieving high recognition accuracy. Therefore, it is expected to help better protection of Tibetan antelopes.