Phase Tracking Research Articles

3D-DIoU: 3D Distance Intersection over Union for Multi-Object Tracking in Point Cloud

Multi-object tracking (MOT) is a prominent and important study in point cloud processing and computer vision. The main objective of MOT is to predict full tracklets of several objects in point cloud. Occlusion and similar objects are two common problems that reduce the algorithm's performance throughout the tracking phase. The tracking performance of current MOT techniques, which adopt the 'tracking-by-detection' paradigm, is degrading, as evidenced by increasing numbers of identification (ID) switch and tracking drifts because it is difficult to perfectly predict the location of objects in complex scenes that are unable to track. Since the occluded object may have been visible in former frames, we manipulated the speed and location position of the object in the previous frames in order to guess where the occluded object might have been. In this paper, we employed a unique intersection over union (IoU) method in three-dimension (3D) planes, namely a distance IoU non-maximum suppression (DIoU-NMS) to accurately detect objects, and consequently we use 3D-DIoU for an object association process in order to increase tracking robustness and speed. By using a hybrid 3D DIoU-NMS and 3D-DIoU method, the tracking speed improved significantly. Experimental findings on the Waymo Open Dataset and nuScenes dataset, demonstrate that our multistage data association and tracking technique has clear benefits over previously developed algorithms in terms of tracking accuracy. In comparison with other 3D MOT tracking methods, our proposed approach demonstrates significant enhancement in tracking performances.

Camera-based Prospective Motion Correction in Paediatric Epilepsy Patients Enables EEG-fMRI Localization Even in High-motion States

Background: EEG-fMRI is a useful additional test to localize the epileptogenic zone (EZ) particularly in MRI negative cases. However subject motion presents a particular challenge owing to its large effects on both MRI and EEG signal. Traditionally it is assumed that prospective motion correction (PMC) of fMRI precludes EEG artifact correction. Methods: Children undergoing presurgical assessment at Great Ormond Street Hospital were included into the study. PMC of fMRI was done using a commercial system with a Moiré Phase Tracking marker and MR-compatible camera. For retrospective EEG correction both a standard and a motion educated EEG artefact correction (REEGMAS) were compared to each other. Results: Ten children underwent simultaneous EEG-fMRI. Overall head movement was high (mean RMS velocity < 1.5 mm/s) and showed high inter- and intra-individual variability. Comparing motion measured by the PMC camera and the (uncorrected residual) motion detected by realignment of fMRI images, there was a five-fold reduction in motion from its prospective correction. Retrospective EEG correction using both standard approaches and REEGMAS allowed the visualization and identification of physiological noise and epileptiform discharges. Seven of 10 children had significant maps, which were concordant with the clinical EZ hypothesis in 6 of these 7. Conclusion: To our knowledge this is the first application of camera-based PMC for MRI in a pediatric clinical setting. Despite large amount of movement PMC in combination with retrospective EEG correction recovered data and obtained clinically meaningful results during high levels of subject motion. Practical limitations may currently limit the widespread use of this technology.

PACR: Pixel Attention in Classification and Regression for Visual Object Tracking

Anchor-free-based trackers have achieved remarkable performance in single visual object tracking in recent years. Most anchor-free trackers consider the rectangular fields close to the target center as the positive sample used in the training phase, while they always use the maximum of the corresponding map to determine the location of the target in the tracking phase. Thus, this will make the tracker inconsistent between the training and tracking phase. To solve this problem, we propose a pixel-attention module (PAM), which ensures the consistency of the training and tracking phase through a self-attention module. Moreover, we put forward a new refined branch named Acc branch to inherit the benefit of the PAM. The score of Acc branch can tune the classification and the regression of the tracking target more precisely. We conduct extensive experiments on challenging benchmarks such as VOT2020, UAV123, DTB70, OTB100, and a large-scale benchmark LaSOT. Compared with other anchor-free trackers, our tracker gains excellent performance in small-scale datasets. In UAV benchmarks such as UAV123 and DTB70, the precision of our tracker increases 4.3% and 1.8%, respectively, compared with the SOTA in anchor-free trackers.

Smart Surveillance System for Illegal Garbage Dumping

Effective garbage management is a key challenge faced by urban areas across the world Garbage dumping in unauthorized places is a common problem in most cities, and it poses a serious threat to public health and the environment. To address this issue, we propose a real-world surveillance platform that detects and reports instances of garbage dumping in unauthorized areas using vision-based action recognition techniques. Our approach involves training a deep neural network on a dataset of garbage dumping actions to recognize and classify instances of this behaviour in real-time video footage. The system operates in three stages detection, tracking, and classification. In the detection phase, we use object detection techniques to locate potential dumping events in video frames. In the tracking phase, we track the detected object across subsequent frames to obtain a trajectory that helps in understanding the context of the action. In the classification phase, we classify the action as garbage dumping or non-dumping using a convolutional neural network. Our system achieves an accuracy of 96.2% on a test dataset, demonstrating its effectiveness in detecting garbage dumping events in real-world surveillance scenarios. The proposed system can be integrated into existing surveillance infrastructure to improve the efficiency of garbage management systems and enhance public health and environmental protection.

Hardware-Efficient, Ultra-Fast and Joint Polarization and Carrier Phase Tracking Scheme Based on Frequency Domain Pilot Tones for DSCM Systems

The coherent digital subcarrier multiplexing (DSCM) has recently been proposed as a cost saving solution to realize flexible and scalable point-to-multipoint (PTMP) networks. In this work, a hardware-efficient, ultra-fast and joint polarization and carrier phase tracking scheme for the DSCM systems based on frequency domain pilot tones (named as PTJ) is proposed and demonstrated via both simulations and experiments. By extracting the amplitude and phase of the pilot tones with a low-pass filter (LPF), the transmission matrix of random birefringence and carrier phase can be obtained prior to subcarrier demultiplexing and channel equalization. For the hardware-efficient implementation, a simplified LPF based on sliding window averaging (SWA) is proposed to filter out the pilot tones. Compared to previous scheme using pilot tones to track polarization and carrier phase in a cascaded manner (named as PTC), our proposed scheme shows better BER performance over wide polarization rotation rates and reduces more than 90% of computation resources by the SWA and joint tracking of polarization and carrier phase. The experimental results show that the proposed scheme can track polarization rotation rate up to 20 Mrad/s with the OSNR penalty of 0.2 dB at 7% FEC threshold. This indicates that an OSNR sensitivity gain of 2.8 dB is achieved compared with the PTC scheme. The proposed scheme provides a hardware-efficient and fast-tracking solution to recovery the polarization and carrier phase for digital subcarrier multiplexing (DSCM) and polarization division multiplexing (PDM) based optical fiber communication system.

Single Shot X-ray Speckle Tracking Phase Contrast Imaging with a Low Brilliance Lab Source

In this paper, we present a single-shot X-ray speckle tracking (XST) phase-contrast imaging (PCI) method for a non-coherent polychromatic laboratory source. XST typically requires a coherent X-ray source, such as a synchrotron, to produce speckle. For a laboratory source without sufficient coherence, the absorption pattern of a random mask, such as sandpaper, have been proposed. However, to track the very small phase shifts in the absorption speckle below the size of the pixels of a standard flat panel detector in the range of 100μm, hundreds of detector images are taken, each moved by a linear stage by a fraction of a pixel to determine the phase shift. As a result, both acquisition time and radiation dose are high. Moreover, precise linear stages are required for sub-pixel movement of the random mask during acquisition of the projection images. In contrast, in this paper we propose a neural network called PCINet to acquire the differential phase image with only one reference image without the sample and one sample image. The proposed system does not require precise linear stages because only a single acquisition is needed. Due to the incoherent source, an absorption-based pseudo-speckle is generated as a reference image. In order to increase the contrast of the pseudo-speckle, a novel, cheap and easy to manufacture tungsten random spatial distrubution of particles is proposed as an alternative to sandpaper. A method for generating realistic training data for the neural network using real X-ray images in a laboratory setup was developed. The training data of the neural network was generated as close as possible to the real data by constructing the input image pairs pixel by pixel from multiple real X-ray images of the pseudo-speckle. The experimental resukts show that it is possible to obtain the differential phase image with only one reference image and one sample image with superimposed absorption speckles in the case of an incoherent laboratory setup.

Change in Descriptive Kinematic Parameters of Patients with Patellofemoral Instability When Compared to Individuals with Healthy Knees—A 3D MRI In Vivo Analysis

Patellofemoral instability (PFI) leads to chronic knee pain, reduced performance and chondromalacia patellae with consecutive osteoarthritis. Therefore, determining the exact patellofemoral contact mechanism, as well as the factors leading to PFI, is of great importance. The present study compares in vivo patellofemoral kinematic parameters and the contact mechanism of volunteers with healthy knees and patients with low flexion patellofemoral instability (PFI). The study was performed with a high-resolution dynamic MRI. In a prospective cohort study, the patellar shift, patella rotation and the patellofemoral cartilage contact areas (CCA) of 17 patients with low flexion PFI were analyzed and compared with 17 healthy volunteers, matched via the TEA distance and sex, in unloaded and loaded conditions. MRI scans were carried out for 0°, 15° and 30° knee flexion in a custom-designed knee loading device. To suppress motion artifacts, motion correction was performed using a moiré phase tracking system with a tracking marker attached to the patella. The patellofemoral kinematic parameters and the CCA was calculated on the basis of semi-automated cartilage and bone segmentation and registrations. Patients with low flexion PFI showed a significant reduction in patellofemoral CCA for 0° (unloaded: p = 0.002, loaded: p = 0.004), 15° (unloaded: p = 0.014, loaded: p = 0.001) and 30° (unloaded: p = 0.008; loaded: p = 0.001) flexion compared to healthy subjects. Additionally, patients with PFI revealed a significantly increased patellar shift when compared to volunteers with healthy knees at 0° (unloaded: p = 0.033; loaded: p = 0.031), 15° (unloaded: p = 0.025; loaded: p = 0.014) and 30° flexion (unloaded: p = 0.030; loaded: p = 0.034) There were no significant differences for patella rotation between patients with PFI and the volunteers, except when, under load at 0° flexion, PFI patients showed increased patellar rotation (p = 0.005. The influence of quadriceps activation on the patellofemoral CCA is reduced in patients with low flexion PFI. Patients with PFI showed different patellofemoral kinematics at low flexion angles in both unloaded and loaded conditions compared to volunteers with healthy knees. Increased patellar shifts and decreased patellofemoral CCAs were observed in low flexion angles. The influence of the quadriceps muscle is diminished in patients with low flexion PFI. Therefore, the goal of patellofemoral stabilizing therapy should be to restore a physiologic contact mechanism and improve patellofemoral congruity for low flexion angles.

Free-running Yb:KYW dual-comb oscillator in a MOPA architecture.

Single-cavity dual-combs comprise a rapidly emerging technology platform suitable for a wide range of applications like optical ranging, equivalent time sampling, and spectroscopy. However, it remains a challenging task to develop a dual-comb system that exhibits low relative frequency fluctuations to allow for comb line resolved measurements, while simultaneously offering high average power and short pulse durations. Here we combine a passively cooled and compact dual-comb solid-state oscillator with a pair of core-pumped Yb-fiber-based amplifiers in a master-oscillator power-amplifier (MOPA) architecture. The Yb:KYW oscillator operates at 250 MHz and uses polarization multiplexing for dual-comb generation. To the best of our knowledge, this is the first demonstration of a single-cavity dual-comb based on this gain material. As the pulse timing characteristics inherent to the oscillator are preserved in the amplification process, the proposed hybrid approach leverages the benefit of both the ultra-low noise solid-state laser and the advantages inherent to fiber amplifier systems such as straight-forward power scaling. The amplifier is optimized for minimal pulse broadening while still providing significant amplification and spectral broadening. We obtain around 1 W of power per output beam with pulses then compressed down to sub-90 fs using a simple grating compressor, while no pre-chirping or other dispersion management is needed. The full-width half-maximum (FWHM) of the radio-frequency comb teeth is 700 Hz for a measurement duration of 100 ms, which is much less than the typical repetition rate difference, making this passively stable source well-suited for indefinite coherent signal averaging via computational phase tracking.

CNN-Based Multi-Object Tracking Networks with Position Correction and IMM in Intelligent Transportation System

Abstract: In multi-object tracking of Intelligent Transportation System, there are objects of different sizes in images or videos, especially pedestrian and traffic lights with low resolution . Meantime, objects are subject to occlusion and loss in object tracking. All of the above mentioned situations may lead to unsatisfactory multi-object tracking results. Attracted by the effect of deep convolution neural networks, the paper proposes a multi-object tracking network, CNN-based Multi-Object Tracking Networks with Position Correction and IMM (CNN_PC_IMM) to solve those problems. Our proposed method consists of object detection module and object tracking module. Compared to other networks, our proposed network has several main contributions that play an essential role in achieving state-of-the-art object tracking performance. In detection phase, feature fusion technique is used. We add a scale branch to the YOLOv3 network to increase the accuracy of small object prediction, and import a residual structure to enhance gradient propagation and avoid gradient disappearance or explosion for the whole network. In addition, we determine the size of the anchor box based on the size of the object in the dataset to better detection and tracking the objects. In tracking phase, IMM is used to calculate the motion state information of the object at a certain moment. Next, the optimization algorithm is proposed to fine-tune object position when the tracking object is occluded due to dense multi-object in traffic scenes or lost due to incomplete object information. Finally, experimental results and analysis are performed on MOT16 benchmark dataset with several popular tracking algorithms used to compare the performance with the proposed algorithm in the paper. It is demonstrated that the proposed algorithm has better performance on MOPA, MOTP, ML.

Experimental Assessment of Generalised Super-Twisting Control for Optimal Reference Tracking in Wave Energy Systems

Maximising wave energy extraction is essential for the successful operation of wave energy converters, and appropriate control strategies play a vital role in achieving this objective. This paper presents a control scheme for an experimental wave energy converter setup. The strategy combines an optimal moment-based reference generation technique with a higher-order sliding mode tracking controller, which provides robust tracking of the associated reference, regardless of the uncertainty present in the experimental operation. The device is tested with two different irregular sea states, and results show that the control structure effectively deals with the system's underlying uncertainty, achieving excellent tracking performance while guiding the system to the corresponding surface following the theoretical phase plot convergence. Furthermore, the comparison with a PID tracking control structure indicates that a proper modification of the tracking element of the loop can improve energy extraction. Finally, consistent tracking error and phase plot evolution behaviour are observed for both sea states.

A Novel SAR Ground Maneuvering Target Imaging Method Based on Adaptive Phase Tracking

A Novel SAR Ground Maneuvering Target Imaging Method Based on Adaptive Phase Tracking

A Three-stage AC side startup strategy for hybrid MMC

When a hybrid modular multilevel converter (MMC) starts from the AC side, the capacitor voltages of full-bridge submodules (FBSMs) will be twice those of half-bridge submodules (HBSMs) in the uncontrolled charging stage due to their structural differences, making it difficult to further charge the SMs in the ensuing controlled charging stage. To solve this problem, a three-stage AC-side startup strategy for hybrid MMCs is proposed. Compared with conventional closed-loop startup strategies, it charges HBSMs and FBSMs simultaneously with the third harmonic injection method, which eliminates the inrush current. And then the HBSMs are charged separately by orthogonal decomposition of the arm voltage after FBSMs are fully charged, which avoids overcharging the FBSMs. Thus, hybrid MMCs can start from the AC side quickly without inrush current, and the unbalance between different SMs is eliminated. The necessity and feasibility of the proposed strategy are discussed in detail. Aiming at possible errors in arm voltage orthogonal decomposition and current phase tracking, control loops for HBSMs and FBSMs are derived and analyzed. Finally, the complete three-stage startup strategy is designed. Simulation results and experimental results are provided to support the theoretical analysis and validate the proposed strategy.

Adaptive optical phase estimation for real-time sensing of fast-varying signals

Optical phase tracking is an important technique for use in high-precision measurement applications, including optical frequency metrology and ground- or space-based gravitational wave observation, and coherent optical communications. When measuring fast-varying real-time signals, the response time limitations of the measurement system’s phase-locked loop cause the best operating point to be mismatched, and the measurement then becomes nonlinear. To make these measurements possible, this work proposes a time delay loop that theoretically enables optimal homodyne detection. When the time delay loop is combined with an extended Kalman filter, the estimated measurement accuracy is improved by 2.4 dB when tracking a fast-varying random signal with a velocity of 107 rad/s. This phase estimation improvement also increases as the interference angle deviates further from the optimal measurement point. The proposed method shows potential for use in real-time sensing and measurement applications.

The effect of electron beam surface remelting on the wear behavior of Ti-6Al-4V by EBF3

Ti-6Al-4V alloy is one of the key materials in the aerospace and chemical industries. Additive manufacturing (AM), e.g., electron beam freeform fabrication (EBF3), is increasingly applied to manufacture the titanium part due to its low cost, high flexibility, high efficiency, etc. At the same time, the wear resistance and hardness of the Ti-6Al-4V alloy synthesized by AM can deteriorate during fabrication. In this paper, electron beam surface remelting (EBSR) is used to improve the wear resistance and hardness of the titanium alloy made by EBF3. The phase, microstructure, element composition, and wear track profile of layers remelted at three EBSR-beam currents were analyzed. According to the results, the synthesized alloy consists of a homogeneous α′ martensitic structure with numerous embedded nano-scale particles rather than a dual α + β lamellar structure when a rapid cooling rate is applied during EBSR. Simultaneously, the coarser prior-β grain boundary was eliminated in the process. The wear rate of the as-obtained remelted layers at the EBSR-beam currents of 0 (as-deposited), 3, 6, and 9 mA was determined as 7.7 × 10−10, 5.7 × 10−10, 7.9 × 10−10, and 8.9 × 10−10 m3/Nm, respectively. The evolution of the structure accounts for the high hardness and superior wear resistance. EBSR successfully modified the as-deposited microstructure to achieve favorable wear properties, which widens the application potential and extends service life.

Recognizing and Classifying Bone Ruptures of the Human Skeletal System Utilizing the Machine Learning Methodologies

Abstract: Rapidly expanding technologies appear every day in various disciplines, particularly medical ones. Nonetheless, there are still distinct outdated approaches that are still widely habituated, effective, and efficient. One of these techniques is the use of X-rays to pinpoint injured bones. However, occasionally the digit of fractures is minor and challenging to see. Procedures should be constructed that are efficient and intelligent. In this analysis, an artificial classification system that recognizes and classifies bone fractures is being designed. There are two major stages in the system that has been conceived. The images of the fractures are processed in the initial stage using eclectic image processing practices to determine their position and shapes. The classification phase tracks, in which a back propagation neural network training on the processed pictures before being put to the trial. The system has experimented with photographs of bone fractures, indicating a high rendition and classification speed.

Ultrafast Laser‐Induced Cathode/Electrolyte Interphase for High‐Voltage Poly(Ethylene Oxide)‐Based Solid Batteries

AbstractPoly(ethylene oxide) (PEO)‐based solid polymer electrolyte promises interfacial compatibility with the high‐capacity metallic anodes in all‐solid‐state batteries (ASSBs). However, the prototype construction is severely hindered by the parasitic ohmic resistance at the electrode‐electrolyte interface, insufficient ionic pathway of the high loading cathode, as well as the PEO oxidation tendency at the high voltage. Herein, a laser‐assisted strategy is presented toward ultra‐efficient cathode modification (completes within 240 s) by constructing continuous, multi‐scale artificial cathode/electrolyte interface (CEI). The tailorable, yet localized temperature gradient induced by the pulsed laser beam can customize the CEI species from the target precursor salts for the on‐demand protection purpose. Derived from the tris(trimethylsilyl)phosphate, the proof‐of‐concept model achieves phosphorus‐rich, ion‐diffusion network across the high‐mass‐loading LiNi0.8Co0.1Mn0.1O2 cathode, which enables the high‐rate operation of the ASSBs prototype as well as the extended shelf life at the oxidized idling state. Transmission‐mode operando X‐ray phase tracking unravels the electrochemical stability origin at the cathode/PEO interface due to the insulation of electron shuttling, where the layered to spinel phase transition and the lattice oxygen release are alleviated. This generic, readily tailorable, highly‐efficient laser processing strategy thus provides unprecedented opportunities to secure the varieties of energy‐dense, polymer‐based ASSBs.

A wide-angle X-ray scattering laboratory setup for tracking phase changes of thin films in a chemical vapor deposition chamber.

The few-layer transition metal dichalcogenides (TMD) are an attractive class of materials due to their unique and tunable electronic, optical, and chemical properties, controlled by the layer number, crystal orientation, grain size, and morphology. One of the most commonly used methods for synthesizing the few-layer TMD materials is the chemical vapor deposition (CVD) technique. Therefore, it is crucial to develop in situ inspection techniques to observe the growth of the few-layer TMD materials directly in the CVD chamber environment. We demonstrate such an in situ observation on the growth of the vertically aligned few-layer MoS2 in a one-zone CVD chamber using a laboratory table-top grazing-incidence wide-angle X-ray scattering (GIWAXS) setup. The advantages of using a microfocus X-ray source with focusing Montel optics and a single-photon counting 2D X-ray detector are discussed. Due to the position-sensitive 2D X-ray detector, the orientation of MoS2 layers can be easily distinguished. The performance of the GIWAXS setup is further improved by suppressing the background scattering using a guarding slit, an appropriately placed beamstop, and He gas in the CVD reactor. The layer growth can be monitored by tracking the width of the MoS2 diffraction peak in real time. The temporal evolution of the crystallization kinetics can be satisfactorily described by the Avrami model, employing the normalized diffraction peak area. In this way, the activation energy of the particular chemical reaction occurring in the CVD chamber can be determined.

Research and application of agricultural energy Internet intelligent system for live streaming E-commerce based on MATLAB analysis in China

This study focus on the agricultural energy Internet, which the concept of “Energy Conservation and Emission Reduction” makes agriculture an essential direction for the development of the energy Internet. Agricultural Energy Internet will change the way energy is produced, transported, and consumed, further affect people’s lives, promote energy transformation, improve energy efficiency, and contribute to the realization of circular economy and sustainable rural development. China has realized the coordinated development of “New agriculture”, “new energy”, and “Live streaming E-commerce” and contributed to the revitalization of rural areas. Based on the problems existing in agricultural energy internet, this study solves the problems existing to ensure the safety and reliability of the photovoltaic power generation system connected to the grid. This study uses the MATLAB model to simulate and analyze the changes in working conditions. The power input can be realized quickly, and the frequency and phase of the power grid can be tracked to meet grid connection requirements. The simulation analysis of SPWM current by MATLAB shows that the control model can quickly realize grid voltage and grid-connected current phase tracking. At 0.06 s, MPPT can be well controlled so that the grid voltage and the grid current are in the same frequency and phase to meet the requirements of the grid. In the energy Internet of agricultural parks, on the one hand, intelligent photovoltaic technology can solve the problem of resource waste in China’s agricultural production and reduce the waste of hydropower resources through more accurate methods than manual observation; On the other hand, photovoltaic power generation and intelligent irrigation can make the use of facility agriculture cleaner and smarter, optimize the agricultural energy structure and reduce labor intensity.

A Fractional-N Synthesizable PLL Using DTC-Based Multistage Injection With Dithering-Assisted Local Skew Calibration

A standard-cell-based fractional-N synthesizable phase-locked loop (PLL) [or multiplying-delay-locked loop (MDLL)] is proposed, where the multiple phases of the three-stage ring digitally controlled oscillator (DCO) are utilized for injection. The required digital-to-time converter (DTC) range is reduced to one third of the DCO’s period, resulting in higher linearity, less jitter, lower power consumption, and smaller area. The issue of the mismatches among DCO’s stages is solved by the proposed dithering-assisted local skew calibration, which removes the skews in the injection path and smears out the periodic pattern at the PLL side to reduce spurs. Most of the dithering noise is suppressed by the injection locking and the phase tracking loop. Measured at 1.0095-GHz output frequency with 24-MHz reference frequency, with the proposed solution, the integrated root-mean-square (rms) jitter can be reduced from 6.40 to 2.55 ps, and the power consumption is 3.36 mW. This translates to −226.6-dB figure of merit (FoM) and −232.8-dB FoM <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">ref</sub> . The measured fundamental fractional spurs range from −56 to −45 dBc.

Autonomous Wristband Placement in a Moving Hand for Victims in Search and Rescue Scenarios With a Mobile Manipulator

In this letter, we present an autonomous method for the placement of a sensorized wristband to victims in a Search-And-Rescue (SAR) scenario. For this purpose, an all-terrain mobile robot includes a mobile manipulator, which End-Effector (EE) is equipped with a detachable sensorized wristband. The wristband consists of two links with a shared shaft and a spring. This configuration allows the wristband to maintain fixed to the EE while moving and get placed around the victim's forearm once the contact is produced. The method has two differentiated phases: i) The visual moving hand tracking phase, where a 3D vision system detects the victim's hand pose. At the same time, the robotic manipulator tracks it with a Model Predictive Controller (MPC). ii) The haptic force-controlled phase, where the wristband gets placed around the victim's forearm controlling the forces exerted. The wristband design is also discussed, considering the magnitude of the force needed for the attachment and the torque the wristband exerts to the forearm. Two experiments are carried out, one in the laboratory to evaluate the performance of the method and the second one in a SAR scenario, with the robotic manipulator integrated with the all-terrain mobile robot. Results show a 97.4% success in the wristband placement procedure and a good performance of the whole system in a large scale disaster exercise.