Space Tracking Research Articles

Third Long-March 5B re-entry campaign through Italian space surveillance radars

The current overpopulation of orbiting objects requires Space Surveillance and Tracking (SST) services. Among these, the monitoring of re-entry events plays a crucial role in ensuring the safety of people and infrastructure on Earth.The work discusses the third Long-March 5B re-entry campaign, which took place from October 31st to November 4th, 2022. This was coordinated, at a European level, by the Space Situational Awareness Centre (C-SSA) of the Italian Air Force (Aeronautica Militare, AM), in collaboration with the AM Flight Test Department, the Italian Space Agency (ASI) and the Astrophysics National Institute (INAF). Support was granted by other Italian institutions, like Politecnico di Milano (PoliMi).Besides the description of the overall re-entry campaign, this work focuses on the innovative contribution given by the Bistatic Radar for LEO survey (BIRALES), an Italian bistatic radar system managed by INAF with the support of PoliMi. Although the challenging off-nominal conditions, BIRALES was capable to acquire observation data throughout the entire campaign, providing both range, range-rate and angular track measurements to the C-SSA. The latter measurements were obtained through a novel approach based on an adaptive beamforming technique, which allows to reach a high-quality track.To obtain a re-entry epoch prediction, orbit determination results are computed starting from the last BIRALES observations without transit prediction, by also including measurements from the MFDR-MR sensor, a tracking radar managed by AM that participated in the campaign. A novel approach is also presented to estimate the ballistic coefficient in a stochastic way, and this estimation is used in both the orbit determination and the re-entry analysis. The re-entry epoch prediction computed in this way is fully consistent with the reference one provided by the U.S. Space Command.

A Novel Algorithm for Precise Orbit Determination Using a Single Satellite Laser Ranging System Within a Single Arc for Space Surveillance and Tracking

A satellite laser ranging (SLR) system uses lasers to measure the range from ground stations to space objects with millimeter-level precision. Recent advances in SLR systems have increased their use in space surveillance and tracking (SST). The problem we are addressing, the precise orbit determination (POD) using one-dimensional range observations within a single arc, is challenging owing to infinite solutions because of limited observability. Therefore, general orbit determination algorithms struggle to achieve reasonable accuracy. The proposed algorithm redefines the cost value for orbit determination by leveraging residual tendencies in the POD process. The tendencies of residuals are quantified as R-squared values using Fourier series fitting to determine velocity vector information. The algorithm corrects velocity vector errors through the grid search method and least squares (LS) with a priori information. This approach corrects all six dimensions of the state vectors, comprising position and velocity vectors, utilizing only one dimension of the range observations. Simulations of three satellites using real data validate the algorithm. In all cases, the errors of the two-line element data (three-dimensional position error of 1 km and velocity error of 1 m/s, approximately) used as the initial values were reduced by tens of meters and the cm/s level, respectively. The algorithm outperformed the general POD algorithm using only the LS method, which does not effectively reduce errors. This study offers a more efficient and accurate orbit determination method, which improves the safety, cost efficiency, and effectiveness of space operations.

The Future of Radar Space Observation in Europe—Major Upgrade of the Tracking and Imaging Radar (TIRA)

The use of near-Earth space has grown dramatically during the last decades, resulting in thousands of active and inactive satellites and a huge amount of space debris. To observe and monitor the near-Earth space environment, radar systems play a major role as they can be operated at any time and under any weather conditions. The Tracking and Imaging Radar (TIRA) is one of the largest space observation radars in the world. It consists of a 34m Cassegrain antenna, a precise tracking radar, and a high-resolution imaging radar. Since the 1990s, TIRA contributes to the field of space domain awareness by tracking and imaging space objects and by monitoring the debris population. Due to new technologies, modern satellites become smaller, and satellite extensions become more compact. Thus, sensitive high-resolution space observation systems are needed to detect, track, and image these space objects. To fulfill these requirements, TIRA is undergoing a major upgrade. The current imaging radar in the Ku band will be replaced by a new radar with improved geometrical and radiometric resolution operating in the Ka band. Due to its wideband fully polarimetric capability, the new imaging radar will increase the analysis and characterization of space objects. In addition, the tracking radar in the L band is also being currently refurbished. Through its novel modular structure and open design, highly flexible radar modes and precise tracking concepts can be efficiently implemented for enhanced space domain awareness. The new TIRA system will mark the start of a new era for space observation with radar in Europe.

CLOWN: The PASO Cloud Detection for Optimization of Automatic Optical Surveys

Orbiting space objects have become in the last decade a major nuisance impacting ground astronomy and orbiting space assets, from observatories to satellites and space stations. In particular with the rise of the satellite population in Low Earth Orbits, space objects are becoming an even bigger threat and a strong problem to astronomical observations. To tackle these threats, several coordinated surveillance networks composed of dedicated sensors (telescopes, radars, and laser ranging facilities) track and survey space objects, from debris to active satellites. As part of the European Space Surveillance & Tracking network, Portugal is developing the Pampilhosa da Serra Space Observatory, with both radio and optical telescopes dedicated to the Space Situational Awareness domain, deployed at a Dark Sky destination. To optimize telescope survey time, we developed CLOud Watcher at Night (CLOWN), an application interface that automatically monitors clouds in real time. This software can correctly trace cloud positions in the sky and provide accurate pointing information to the observation planning of the optical telescope to avoid cloudy areas. CLOWN only requires the use of an all-sky camera, which is already a norm in observatories with optical telescopes and can be used with any camera, including those for which no information about its model specification do exist. CLOWN does not require great computing power, and it does not require the installation of additional equipment. CLOWN results are very promising and confirm that the app can correctly identify clouds in a variety of different conditions and cloud types.

Control system design for azimuth position of earth station antennas

Smart earth station antennas have been used for several decades in many applications, from satellite communications to space object detection and tracking. The accuracy of the azimuth position for such antennas plays a crucial role in most steerable ground station antennas. Satellite tracking and space object detection demand precise tracking capabilities from the Earth. Several methods and techniques have been developed and used in industry to control the directions of ground station antennas, including the azimuth position. The challenge of azimuth tracking is increasing with the demand for full-sky coverage and with the exponential increase in space objects, including man-made satellites and operational and nonoperational objects; thus, providing accurate tracking is a key technology that demands continuous enhancement and development. This article presents the use of a PID-proportional-integral-derivative controller, a slide mode controller and a fractional order PID controller. It also introduces a new methodology based on model predictive control (MPC). The manuscript provides the core design for each of these controllers and provides insight into the performance of each controller even in the presence of disturbance. The camel optimization algorithm (COA) was used to obtain the optimal design parameters of each controller in the considered scenarios.

Robot target tracking control considering obstacle avoidance based on combination of deep reinforcement learning and PID

When simultaneously addressing the challenges of dynamic target tracking and obstacle avoidance for robots, conventional control and control only based on reinforcement learning cannot deal with the complex scenarios effectively. The purpose of this study is to design a robot control algorithm that combines deep reinforcement learning (Soft Actor-Critic, SAC) with PID to achieve real-time tracking of a moving object and effectively avoid single or multiple obstacles. The control of the robot is divided into two key components: initially, the first joint of the 6-degree-of-freedom robot is controlled by PID algorithm, which makes the working plane (the plane coincident with the axis of the first joint and parallel to the linkage) quickly approach the target until it overlaps. Subsequently, the task of reinforcement learning is simplified to control the planar robot to track the target projection in working plane while avoiding the obstacle projection, ultimately achieve target tracking and obstacle avoidance in 3D space. The simulation and experiment results show that the proposed method has good efficiency and convergence speed. The SAC-PID strategy effectively controls the Universal-Robots UR5 to complete dynamic target tracking while accomplishing obstacle avoidance in both virtual and real-world environments.

Future activities in the near-earth space in the face of ever-increasing space traffic

The increasing launch rate of spacecraft, particularly due to the deployment of large constellations and miniaturized satellites in Low Earth Orbit (LEO), has led to a significant rise in space traffic and debris. This paper examines emerging technologies and strategies for future Space Traffic Management (STM) to ensure sustainable operations in space. Key focus areas include the use of artificial intelligence (AI) for enhanced Collision Avoidance (CA) systems, the development of advanced Space Surveillance and Tracking (SST) capabilities, and Active Debris Removal (ADR) techniques to mitigate the growing risks associated with space debris. Additionally, the paper explores the potential of in-orbit servicing, re-entry services, and the exploitation of Very Low Earth Orbits (VLEO) and cislunar space. The integration of these technologies and practices is essential to manage the anticipated growth in space activities while minimizing collision risks and ensuring the long-term sustainability of the space environment.

Too-Short-Arc Association and Clustering Method for Space-Based Optical Observations

Space-based optical observation is assuming an increasingly significant role in space surveillance and tracking. However, it often yields tracks that are too short, which are known as too short arcs (TSAs). A single TSA lacks sufficient information for reliable initial orbit determination of a resident space object. Therefore, it is typically necessary to perform tracklet association during catalog building and maintenance. This study presents a novel tracklet association method that improves upon existing techniques by combining admissible regions and nonlinear orbital uncertainty propagation. Proceeding by constructing TSA association matrices and TSA clustering matrices, the bond energy algorithm, traditionally employed in the design of distributed database systems, is applied to cluster TSAs based on the association results between two arbitrary TSAs. Furthermore, the proposed splitting algorithm reduces the computational load associated with clustering multiple tracklets and effectively handles erroneous association results. To assess the effectiveness of this approach, it was tested in a space-based optical-survey scenario, accounting for practical observation uncertainties. The simulation results demonstrate that the method achieves a high level of accuracy in both TSA association and clustering.

Tracking performances of the ePIC detector at the Electron-Ion Collider

The ePIC (electron–Proton/Ion Collider) experiment is a future facility at the Electron-Ion Collider (EIC) complex, located at the Brookhaven National Laboratory, USA. It will use ∼70% longitudinally polarized beam of electrons, protons, and light ions to study their collisions to understand the properties of the quarks, gluons, and the strong force responsible for the formation of the nucleus. The layout of the central detector of the ePIC experiment is not symmetric along the beams axis consisting of barrel, forward, and backward detectors to achieve a wide pseudorapidity (|η|< 3.5) coverage. There are further far-forward and far-backward tracking detectors to measure the luminosity and reconstruct the particles and fragments for the study of the exclusive deep-inelastic scattering (DIS) processes. The experiment has a challenging environment due to the presence of the background radiations (synchrotron radiation, beam-gas interactions, minimum-bias events, etc.) which will produce additional background hits on the tracker. The synchrotron radiation is suppressed to some extent by coating the beampipe with a 5μm gold layer. The experiment uses state-of-the-art bent wafer-scale silicon monolithic active pixel sensors (MAPS) with a ∼5μs acquisition window, micro-pattern gas detector (MPGD) with a good time resolution (∼20–30ns), and time-of-flight detectors based on AC-LGAD sensors (time resolution ∼30ps). The timing information of each detector will play a crucial role in track finding and rejecting the background hits utilizing the 4-dimensional tracking (space, time) to ensure the excellent performance of the experiment. The article presents the expected tracking performance of the ePIC detector using the modular ePIC software stack for simulation, reconstruction, and analysis. The Geant4 toolkit is employed for full detector simulations, alongside DD4hep (Detector Description for High Energy Physics) for geometry definition and exchange. The reconstruction incorporates the JANA2 framework, in addition to the tracking and vertexing algorithms inherited from A Common Tracking Software (ACTS).

Studying Drosophila Larval Behavior in Agarose Channels.

Larvae of the fruit fly Drosophila melanogaster are a popular and tractable model system for studying the development and function of sensorimotor circuits, thanks to the relative numerical simplicity of their nervous system and the wealth of available genetic tools to manipulate the anatomy, activity, and function of specific cell types. Researchers studying the role of a particular gene or cell type in sensorimotor circuit activity or function may wish to observe the effects of an experimental manipulation during behavior in the intact animal. Observing these effects, which may include changes in the intracellular calcium concentration or movement of small numbers of neurons, muscles, etc., typically requires high-spatial-resolution imaging, which poses several difficulties in the freely crawling larva. Freely crawling larvae can move quickly and with changeable heading, making manual or automatic tracking challenging; additionally, they may make three-dimensional movements, such as rearing, that can degrade imaging focus. These challenges are potentially solvable using advanced imaging and algorithmic tracking setups, but cost, space, or development time may be prohibitive. This protocol describes a simple and cost-effective method for placing larvae inside agarose channels, thereby restricting larval crawling to a single dimension and enabling higher-magnification time-series imaging of fluorescently labeled structures during many cycles of locomotion. By using larvae that express fluorescent calcium indicators in cells of interest, researchers can apply this method to study the effects of experimental manipulations on neural or muscular activity during behavior in the intact animal.

A Multidimensional Neural Representation of Face Impressions.

From a glimpse of a face, people form trait impressions that operate as facial stereotypes, which are largely inaccurate yet nevertheless drive social behavior. Behavioral studies have long pointed to dimensions of trustworthiness and dominance that are thought to underlie face impressions due to their evolutionarily adaptive nature. Using human neuroimaging (N = 26, 19 female, 7 male), we identify a two-dimensional representation of faces' inferred traits in the middle temporal gyrus (MTG), a region involved in domain-general conceptual processing including the activation of social concepts. The similarity of neural-response patterns for any given pair of faces in the bilateral MTG was predicted by their proximity in trustworthiness-dominance space, an effect that could not be explained by mere visual similarity. This MTG trait-space representation occurred automatically, was relatively invariant across participants, and did not depend on the explicit endorsement of face impressions (i.e., beliefs that face impressions are valid and accurate). In contrast, regions involved in high-level social reasoning (the bilateral temporoparietal junction and posterior superior temporal sulcus; TPJ-pSTS) and entity-specific social knowledge (the left anterior temporal lobe; ATL) also exhibited this trait-space representation but only among participants who explicitly endorsed forming these impressions. Together, the findings identify a two-dimensional neural representation of face impressions and suggest that multiple implicit and explicit mechanisms give rise to biases based on facial appearance. While the MTG implicitly represents a multidimensional trait space for faces, the TPJ-pSTS and ATL are involved in the explicit application of this trait space for social evaluation and behavior.

A Robust AR-DSNet Tracking Registration Method in Complex Scenarios

A robust AR-DSNet (Augmented Reality method based on DSST and SiamFC networks) tracking registration method in complex scenarios is proposed to improve the ability of AR (Augmented Reality) tracking registration to distinguish target foreground and semantic interference background, and to address the issue of registration failure caused by similar target drift when obtaining scale information based on predicted target positions. Firstly, the pre-trained network in SiamFC (Siamese Fully-Convolutional) is utilized to obtain the response map of a larger search area and set a threshold to filter out the initial possible positions of the target; Then, combining the advantage of the DSST (Discriminative Scale Space Tracking) filter tracker to update the template online, a new scale filter is trained after collecting multi-scale images at the initial possible position of target to reason the target scale change. And linear interpolation is used to update the correlation coefficient to determine the final position of target tracking based on the difference between two frames. Finally, ORB (Oriented FAST and Rotated BRIEF) feature detection and matching are performed on the accurate target position image, and the registration matrix is calculated through matching relationships to overlay the virtual model onto the real scene, achieving enhancement of the real world. Simulation experiments show that in complex scenarios such as similar interference, target occlusion, and local deformation, the proposed AR-DSNet method can complete the registration of the target in AR 3D tracking, ensuring real-time performance while improving the robustness of the AR tracking registration algorithm.

Objective Neighborhood-Level Disorder Versus Subjective Safety as Predictors of HIV Transmission Risk and Momentary Well-Being

Mental health and HIV risk behavior have been studied with ecological momentary assessment (EMA), but this approach has not been combined with tracking of activity space (where people go and what they encounter there) in people with HIV and their social relations, who may be HIV+ or HIV−. Activity space represents a modifiable risk or protective factor for behavior related to health status and quality of life, in both clinical and nonclinical populations. We conducted an observational study with 286 participants (243 HIV+ and 43 HIV−), roughly matched for socioeconomic status and neighborhood of residence via three waves of snowball sampling. Each participant carried a smartphone for up to 4 weeks, making 5 randomly prompted entries and 1 end-of-day entry each day, plus self-initiated event-contingent entries for sexual activity and drug use. Responses to randomly prompted items provided subjective evaluations of the safety of the participant’s current social and physical environment (the place they were and the people they were with). GPS-based location tracking—coupled with publicly available statistic indicating neighborhood-level physical disorder and socioeconomic disadvantage—provided an indicator of each participant’s exposure to objective psychosocial hazard. We examined possible relationships of these objective and subjective environmental exposures with risky sexual and intravenous drug-use behavior, knowledge and utilization of antiretroviral treatment and prophylaxis, and momentary mental health (mood and stress, which relate to risky behavior and overall well-being). We found that both risky behavior and mental health were more related to participants’ subjective evaluations of their activity space than to objective measures of neighborhood-level disorder, suggesting that, even within an objectively hazardous neighborhood, people who find a niche they perceive as socially and physically safe may engage in less risky behavior and have better well-being.Trial registration Clinicaltrials.gov Identifier NCT01571752.

Synthesis, characterization, and CO sensing properties of NiO thin film for commercial aircraft applications

Abstract The detection of combustion gases such as carbon monoxide (CO) and fuel leaks is a concern in regard to aeronautical safety and has led to the development of semiconductor sensors. The focus of this work is the detection of CO within commercial aircraft using a thin film of nickel oxide (NiO) as the sensing element. The NiO phase was synthesized using the sol-gel method using a modification of the procedures proposed by N. Talebian and B. Pejova. Microstructural characterization of the NiO thin film was performed using scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM). Optical analysis was carried out using diffuse reflectance (UV-VIS) spectroscopy. The results showed that the NiO thin film was homogeneous and composed of nodular nanoparticles with size between 10 and 15 nm and thickness of 75 nm. The band gap value was 3.3 eV, which is consistent with p-type semiconductors. The sensitivity of the devices was determined by means of the static environment method. The best operation temperature was 200°C for the device with 100-µm spacing between tracks, which gave a response time of 165 seconds and recovery time of 212 seconds according the results of a flow-through method. The device with this track spacing is ideal for CO detection at 50 ppm, at which the first symptoms of intoxication appear in humans inside commercial aircraft.

Iterative flexibility compensation based high precision trajectory tracking for industrial manipulators

High precision industrial manipulators are widely demanded in precision machining and advanced manufacturing. To realize high precision trajectory tracking in task space, feedback plus model based feedforward control strategies are widely used in modern industrial manipulators. Furthermore, the accuracy of feedforward model determines the accuracy of trajectory tacking to a great extent, especially for elastic manipulators. In traditional feedforward controllers, the flexibilities out of the rotational plane are often neglected and thus the end-effector tracking performance can be degraded a lot. Therefore, an iterative flexibility compensation based feedforward controller is proposed to improve the end-effector trajectory tracking accuracy of industrial manipulators in this paper. First, the flexible deformations in all directions are described accurately by using the extended flexible joint model (EFJM) for industrial manipulators. Second, a feedforward controller is designed by using the dynamic inversion of EFJM. In the feedforward controller, an iterative flexibility compensation scheme is designed to transform the reference Cartesian trajectory into joint space and thus the limitation of the nonminimum phase characteristics of EFJM can be avoided. Moreover, the flexible deformations are predicted and compensated based on EFJM. After that, the feedforward torque is derived in joint space by using the efficient feedforward torque computation algorithm for EFJM. Simulation and experimental results demonstrate the effectiveness of the proposed method.

Влияние технологических параметров процесса прямого лазерного выращивания на качество формируемого объекта из титанового сплава ВТ23

Introduction. Laser engineered net shaping (LENS) or Direct metal deposition (DMD) is considered as a promising method for manufacturing products of complex configurations from titanium-based alloys, as it allows minimizing the use of machining and loss of material to waste. Currently, neither the LENS technological process of titanium alloy VT23 has not been developed, nor the structural features of the alloy after LENS have not been studied, which will make it possible to determine the scope of application of the material after LENS. The purpose of this study is to determine optimal modes of the LENS process for manufacturing of quality parts from titanium alloy VT23. Methodology. The alloy specimens obtained with laser power 700÷1300 W in increments of 100 W and scanning speed 600÷1,000 mm/min in increments of 200 mm/min and distance between adjacent laser tracks 0.5–0.9L (L — track width) in increments of 0.2L were analyzed in the study. The elemental composition of the powder material was studied by X-ray fluorescence analysis and reducing combustion in a gas analyzer, the structure of the objects obtained by LENS was analyzed by metallographic and X-ray phase analysis methods as well as microhardness was determined. Results and discussion. It is established that high-quality objects without cracks, with low porosity can be synthesized from VT23 alloy by LENS method using the following modes: laser power 700÷1100 W, scanning speed 800–1,000 mm/min, track spacing 0.5–0.7 of the individual track width L. It is shown that after all investigated LENS modes, the VT23 alloy had a dispersed (α+β) structure of the “basket weave” type. It is revealed that regardless of LENS mode the amount of β-phase in the alloy structure is about 30 %. It is shown that the microhardness of the deposited material does not depend on LENS modes and is 460 HV.

Operational Angular Track Reconstruction in Space Surveillance Radars through an Adaptive Beamforming Approach

In the last few years, many space surveillance initiatives have started to consider the problem represented by resident space object overpopulation. In particular, the European Space Surveillance and Tracking (EUSST) consortium is in charge of providing services like collision avoidance, fragmentation analysis, and re-entry, which rely on measurements obtained through ground-based sensors. BIRALES is an Italian survey radar belonging to the EUSST framework and is capable of providing measurements including Doppler shift, slant range, and angular profile. In recent years, the Music Approach for Track Estimate and Refinement (MATER) algorithm has been developed to retrieve angular tracks through an adaptive beamforming technique, guaranteeing the generation of more accurate and robust measurements with respect to the previous static beamforming approach. This work presents the design of a new data processing chain to be used by BIRALES to compute the angular track. The signal acquired by the BIRALES receiver array is down-converted and the receiver bandwidth is split into multiple channels, in order to maximize the signal-to-noise ratio of the measurements. Then, the signal passes through a detection block, where an isolation procedure creates, for each epoch, signal correlation matrices (CMs) related to the channels involved in the detection and then processes them to isolate the data stream related to a single detected source. Consequently, for each epoch and for each detected source, just the CM featuring the largest signal contribution is kept, allowing deriving the Doppler shift measurement from the channel illumination sequence. The MATER algorithm is applied to each CM stream, first estimating the signal directions of arrival, then grouping them in the observation time window, and eventually returning the target angular track. Ambiguous estimates may be present due to the configuration of the receiver array, which cause spatial aliasing phenomena. This problem can be addressed by either exploiting transit prediction (in the case of cataloged objects), or by applying tailored criteria (for uncatalogued objects). The performance of the new architecture was assessed in real operational scenarios, demonstrating the enhancement represented by the implementation of the channelization strategy, as well as the angular measurement accuracy returned by MATER, in both nominal and off-nominal scenarios.

Performance and Navigation Behavior of using Teleportation in VR First-Person Shooter Games

Teleportation has been adopted as the preferred mode of navigation in many virtual reality (VR) experiences due to its ability to allow users to easily move beyond the limitations of the tracking space while minimizing the risk of inducing VR sickness. Teleportation instantly translates the user’s viewpoint to a user-selected destination and therefore eliminates any optical flow generation that could cause visual-vestibular conflict. Though teleportation is a discrete navigation method unique to the domain of VR, most VR experiences are modeled after 3D experiences found on desktop/console platforms that use continuous locomotion. How the use of teleportation affects the performance and navigation behavior of its users, especially in competitive first-person shooter environments is unknown, yet it could have a significant effect on gameplay design. We conducted a user study (n=21) that compares teleportation versus continuous locomotion using a VR first-person shooter game with other players being simulated using AI agents. We found significant differences in performance, navigation behavior, and how both locomotion methods are perceived by its users. Specifically, using teleportation, players traveled farther, but during combat were found to be more stationary and as a result got hit more frequently. These differences were profound and carry the potential to impact multiplayer games. We discuss possible strategies to balance gameplay.

AS-T[formula omitted]BP: An efficient assignment scheme for space TT&C tasks with bidirectional privacy-preserving under blockchain architecture

In recent years, the space Tracking Telemetry and Command (TT&C) network has attracted much attention because it can provide users with secure and convenient information services. However, there are still challenges in achieving efficient task assignments and providing privacy-preserving for both TT&C parties in precise space TT&C services. In this paper, we propose an efficient blockchain-based task assignment scheme (AS-T3BP) in space TT&C network. Specifically, we introduce authorized privacy set intersection to ensure bidirectional privacy security for task requesters and performers and integrate an improved cuckoo filter algorithm to achieve batch assignment for tasks. And AS-T3BP allows the executor to customize the access policies of TT&C information flexibly, and only authorized satellites can access the information and verify the assignment results. For tasks that fail to be assigned, we propose a distributed and credible task reassignment method, which publishes the tasks on the blockchain built by the TT&C base station, thereby ensuring the real-time and accuracy of task assignments. Performance analysis shows that AS-T3BP is effective and can minimize misinform rates and reassignment rates of 23.39% and 8.85%, alleviate the problem of inefficient task assignment, and still maintain system stability.

Port-Hamiltonian modeling and jumping trajectory tracking control for a bio-inspired quadruped robot

Applying jumping locomotion into autonomous mobile robot is an effective way for improving abilities to overcome barriers and pass through complex terrains. In this paper, based on the designed structural framework for bio-inspired quadruped jumping robot, dynamic model is established by utilizing port-Hamiltonian with dissipation (pHd) method, and a passivity-based control strategy for the robot joints trajectory tracking is presented. First, morphology and biomimetics knowledges of frogs (a kind of animals with excellent jumping skill) motivate us to complete a bio-inspired jumping robot framework based on frog’s motion mechanism and body structure with torsional springs as energy storage device. Then, combining system passivity and dissipation, port-Hamiltonian method is utilized to build a dynamic model for expressing the relationship of energy and force in the designed robot. Jumping process analysis of different stages is also designed for ensuring the robot to complete taking-off and landing stages successfully. Next, with the definition of extending feasible robotic joint trajectory by La Salle invariant set principle, interconnection and damping assignment passivity-based control (IDA-PBC) method is exerted to obtain a trajectory controller for realizing smoothly and stably trajectory tracking in joint space. At last, simulation results show the reasonableness of the designed framework. By comparing our method with state-feedback and sliding mode control, effectiveness of the dynamic model and trajectory controller is also verified.