Unified Motion Research Articles

Motion Control of a Hybrid Quadruped-Quadrotor Robot

Multimodal motion capability is an emerging topic in the robotics field, and this paper presents a hybrid robot system maneuvering in both terrestrial and aerial environments. Firstly, a micro quadruped–quadrotor robot with onboard sensing and computing is developed. This robot incorporates both the high mobility of unmanned aerial vehicles and the long endurance of mobile robots on the ground. A coordinated motion control scheme is then exploited for adaptive terrestrial–aerial motion transition. In this scheme, a bio-inspired terrestrial locomotion controller is proposed to generate various quadruped locomotions, and a model-based aerial locomotion controller is proposed to generate various quadrotor configurations. Then, an unified motion controller for the two subsystems which dynamically adjusts crawling and flying motion in a complicated environment is presented. Consequently, several practical trials are conducted to demonstrate the adaptability and the robustness of the proposed system.

A Unified Motion Generation Approach for Quadruped L-S Walk and Trot Gaits Based on Linear Model Predictive Control

A Unified Motion Generation Approach for Quadruped L-S Walk and Trot Gaits Based on Linear Model Predictive Control

A Unified Motion Modeling Approach for Snake Robot's Gaits Generated With Backbone Curve Method

A Unified Motion Modeling Approach for Snake Robot's Gaits Generated With Backbone Curve Method

Unified Motion Planner for Walking, Running, and Jumping Using the Three-Dimensional Divergent Component of Motion

Unified Motion Planner for Walking, Running, and Jumping Using the Three-Dimensional Divergent Component of Motion

Unified Motion Control for Multilift Unmanned Rotorcraft Systems in Forward Flight

Interest in multilift rotorcraft systems has reemerged in recent years to overcome some of the problems in single unmanned aerial vehicle handling and delivery systems. Using multiple unmanned rotorcrafts (URs), the load weight can be evenly distributed among the vehicles, extending the flight time and therefore increasing the working distance of such systems. Moreover, with a slung-load configuration, bigger size packages with complex shape and equipment that may interfere with the onboard electronics can be carried. In this context, this article presents a payload-based unified motion control that allows any number of URs to cooperatively transport a slung load in forward flight. The motion control comprises path-following and trajectory-tracking algorithms, considers obstacle avoidance, implements a specific strategy for load weight distribution (load equalization) by regulating the relative altitude of each UR, and is robust to disturbances such as wind. In addition, this work shows that load equalization is essential for slung-load cooperative transport, especially in forward flight. The controller’s stability is analytically studied and the good performance of the system is demonstrated through exhaustive simulations using validated dynamic models for mini-helicopters, cables, and payload. Finally, the relation between load weight and number of URs is analyzed by considering several scenarios.

M2C-GVIO: motion manifold constraint aided GNSS-visual-inertial odometry for ground vehicles

Visual-Inertial Odometry (VIO) has been developed from Simultaneous Localization and Mapping (SLAM) as a low-cost and versatile sensor fusion approach and attracted increasing attention in ground vehicle positioning. However, VIOs usually have the degraded performance in challenging environments and degenerated motion scenarios. In this paper, we propose a ground vehicle-based VIO algorithm based on the Multi-State Constraint Kalman Filter (MSCKF) framework. Based on a unified motion manifold assumption, we derive the measurement model of manifold constraints, including velocity, rotation, and translation constraints. Then we present a robust filter-based algorithm dedicated to ground vehicles, whose key is the real-time manifold noise estimation and adaptive measurement update. Besides, GNSS position measurements are loosely coupled into our approach, where the transformation between GNSS and VIO frame is optimized online. Finally, we theoretically analyze the system observability matrix and observability measures. Our algorithm is tested on both the simulation test and public datasets including Brno Urban dataset and Kaist Urban dataset. We compare the performance of our algorithm with classical VIO algorithms (MSCKF, VINS-Mono, R-VIO, ORB_SLAM3) and GVIO algorithms (GNSS-MSCKF, VINS-Fusion). The results demonstrate that our algorithm is more robust than other compared algorithms, showing a competitive position accuracy and computational efficiency.

Adaptive Capacitor Voltage-Based Model Predictive Control for Open-Winding PMSM System With a Floating Capacitor

In this article, an adaptive capacitor voltage-based model predictive control (ACV-MPC) strategy for the open-winding permanent magnet synchronous motor system with a floating capacitor (FC-OW-PMSM) is proposed. The control precision of the conventional model predictive control (CMPC) strategy is improved by adjusting the capacitor voltage without using high switching frequency methods. The position of voltage vectors (VVs) is uncertain under different capacitor voltages. To establish a unified motion process of the uncertain VVs, the VV trajectories are analyzed. Furthermore, a novel region division scheme is proposed to locate the candidate VV trajectory. To further determine the reference capacitor voltage and select the candidate VVs from the candidate VV trajectory, the proposed scheme is analyzed in each VV trajectory. Finally, a cost function with only one capacitor voltage constraint is carried out to select the optimal VV, and thus, the weighting factors and the complicated iterative process are both avoided. Experimental studies are carried out to verify the effectiveness of the proposed strategy.

Adaptive adjustable fast marching square method based path planning for the swarm of heterogeneous unmanned surface vehicles (USVs)

In the process of deploying multiple unmanned surface vehicles (USVs) to work collaboratively, path planning is s an essential component. A team of USVs that perform joint missions, may have heterogeneity in the draft, endurance, dynamic characteristics, etc. If the path planning for each USV in the swarm is carried out separately, it is not only time-consuming but also difficult to ensure the unity of the entire swarm. So, a path planning method for the whole swarm is studied herein and how to take the aforesaid heterogeneities of USVs into consideration during the path planning is the main focus of the paper. The unified motion model of the heterogeneous USV swarm and the model representing the heterogeneities of USVs are given firstly, which is the baseline of the following content. Then, the fundamental of the fast marching square (FMS) method is elaborated, and the cutoff threshold function Sat(x) is added to the FMS method to adjust the potential field of the FMS so that different paths can be obtained. The adaptive adjustable fast marching square (AAFMS) method is proposed later, and its core idea is to adjust the potential field of the FMS to generate the desired path that meets the needs of heterogeneous USVs. Afterwards, the potential field is adjusted further to make the planned path comply with the International Regulations for Preventing Collisions at Sea (COLREGs), which also improves the applicability of the proposed path planning method in practical applications. Comparative simulation results demonstrate the effectiveness of the proposed method.

Coordinated control of the heterogeneous unmanned surface vehicle swarm based on the distributed null-space-based behavioral approach

Deployment of multiple unmanned surface vehicles (USVs) to execute tasks collaboratively has been acknowledged with greater attention in recent years. On this basis, this paper presents a coordinated control approach for a swarm of multiple heterogeneous unmanned surface vehicles (USVs) based on a distributed null-space-based behavioral (NSB) method. A unified motion model is established first to describe the kinematic characteristics of heterogeneous USVs. According to the differences in the ship types and kinetics of USVs, the swarm is divided into different sub-swarms and an NSB-based coordinated control approach having a distributed structure is proposed combined with behaviors that comply with the International Regulations for Preventing Collisions at Sea (COLREGs) to make it more suitable for practical applications. The concept of the virtual leader and the line-of-sight (LOS) guidance law are incorporated into the distributed NSB method, so, in the process of coordinated control, the USV sub-swarms can also be guided to navigate along the given desired path synchronously. Furthermore, a low-cost fusion positioning method is proposed herein to facilitate the implementation of the coordinated control approach in practice. The effectiveness of the proposed coordinated control approach is quantized and verified by simulations and real experiments.

Dual-Arm Control for Coordinated Fast Grabbing and Tossing of an Object: Proposing a New Approach

Picking up objects and tossing them on a conveyor belt are activities generated on a daily basis in industry. These tasks are still done largely by humans. This article proposes a unified motion generator for a bimanual robotic system that enables two seven-degree-of-freedom robotic arms to grab and toss an object in one swipe. Unlike classical approaches that grab the object with quasi-zero contact velocity, the proposed approach is able to grasp the object while in motion. We control the contact forces prior to and following impact so as to stabilize the robots’ grip on the object. We show that such swift grasping speeds up the pick-and-place process and reduces energy expenditure for tossing. Continuous control of the reach, grab, and toss motion is achieved by combining a sequence of time-invariant dynamical systems (DSs) in a single control framework. We introduce a state-dependent modulation function to control the generated velocity in different directions. The framework is validated in simulation and on a real dual-arm system. We show that we can precisely toss objects within a workspace of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${0.2}\,{\times}\,{0.4}{\text{m}}^{2}$</tex-math></inline-formula> . Moreover, we show that the algorithm can adapt on-the-fly to changes in object location.

Autonomous and Adaptive Navigation for Terrestrial-Aerial Bimodal Vehicles

Terrestrial-aerial bimodal vehicles bloom in both academia and industry because they incorporate both the high mobility of aerial vehicles and the long endurance of ground vehicles. In this work, we present an autonomous and adaptive navigation framework to bring complete autonomy to this class of vehicles. The framework mainly includes 1) a hierarchical motion planner that generates safe and low-power terrestrial-aerial trajectories in unknown environments and 2) a unified motion controller which dynamically adjusts energy consumption in terrestrial locomotion. Extensive real-world experiments and benchmark comparisons are conducted on a customized robot platform to validate the proposed framework’s robustness and performance. During the tests, the robot safely traverses complex environments with terrestrial-aerial integrated mobility, and achieves <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$7\times$</tex-math></inline-formula> energy savings in terrestrial locomotion. Finally, we will release our code and hardware configuration for the reference of the community.

Investigations on the micro-interactions of grit-workpiece and forces prediction in ultrasonic vibration side grinding of optical glass

The cutting force in ultrasonic vibration side grinding (UVSG) of brittle materials is of significance for the machined quality. However, the micro-interaction mechanism between abrasive grits and workpiece remains a significant issue in terms of the research on cutting forces in the brittle material grinding due to the stochastic distribution nature of the grits. Meanwhile, these micro-interactions are further affected by ultrasonic vibration in UVSG process. Considering these issues, this paper aims at modeling the cutting force affected by the stochastically distributed grits and ultrasonic vibration to reveal the multi-scale grinding mechanics in UVSG of optical glass. Through modeling the stochastic grinding wheel surface and analyzing the kinematics of multi-grits, the unified motion trajectory and the instantaneous chip thickness in UVSG were enabled to derived to determine the different grit-workpiece interaction stages. With consideration of the ultrasonic vibration effects on the micro-interactions, a novel theoretical cutting force model was developed based on the analysis of force generated at three interaction stages, i.e., rubbing, plowing, and cutting stages. The numerical simulations of this model could provide the time-domain variation features of cutting forces to evaluate the fluctuations and trends of the cutting forces from multi-scales. Experimental verifications indicated that the cutting force and its fluctuations are within the acceptable error margin. Furthermore, a thorough analysis of force fluctuating situations at different ultrasonic vibration amplitudes was conducted. The analytical results indicated that an increase in ultrasonic vibration amplitude was not only beneficial to restrain the force fluctuation, but helpful to reduce the brittle fracture damages of optical glass. The evolution trend of cutting force in different grinding conditions and wheel specifications were discussed in detail to reveal the influence mechanisms of machining parameters on the cutting forces. Afterwards, the detection results of ground workpieces demonstrate that the introduction of ultrasonic vibration would improve the machined quality of optical glass in UVSG process.

Amplitude Control of Stall-Induced Nonlinear Aeroelastic System Based on Iterative Learning Control and Unified Pitch Motion

In this study, vibration control, a behavior which subordinates to stall-induced nonlinear vibration and amplitude control of a wind turbine’s blade section, based on unified pitch motion driven by slider-linkage mechanism, is investigated by using an iterative learning control (ILC) method. The nonlinear dynamical system is a nonlinear aeroelastic system. The aeroelastic system equations consist of three parts: the nonlinear structural equations derived by using Lagrange’s equations, the improved stall-induced nonlinear ONERA (ISNO) aerodynamic equations, and the pitch control equation. The ISNO model is not only suitable for the actual external pitch motion, but also suitable for the solution by using an ILC algorithm due to its fitted nonlinear aerodynamic coefficients. The ILC algorithm used here is an improved iterative learning algorithm (IILC) which considers the large-range, linearized, residual terms, and realizes gain adaptive tuning based on PID controller. On the one hand, it can control the amplitude of an unsteady flutter through trajectory tracking. On the other hand, when the preset value of the amplitude of the ideal trajectory is very small, it can make the system directly tend to convergence and stability of a nonlinear aeroelastic system. To simplify the extremely difficult iterative process, the pitch movement can track the elastic twist displacement in time, thus simplifying the aeroelastic equations and accelerating the IILC iteration process. Therefore, amplitude control for flap-wise/lead-lag displacements is realized by the unified pitch motion and the trajectory tracking controlled by using the IILC algorithm.

MDPET: A Unified Motion Correction and Denoising Adversarial Network for Low-Dose Gated PET.

In positron emission tomography (PET), gating is commonly utilized to reduce respiratory motion blurring and to facilitate motion correction methods. In application where low-dose gated PET is useful, reducing injection dose causes increased noise levels in gated images that could corrupt motion estimation and subsequent corrections, leading to inferior image quality. To address these issues, we propose MDPET, a unified motion correction and denoising adversarial network for generating motion-compensated low-noise images from low-dose gated PET data. Specifically, we proposed a Temporal Siamese Pyramid Network (TSP-Net) with basic units made up of 1.) Siamese Pyramid Network (SP-Net), and 2.) a recurrent layer for motion estimation among the gates. The denoising network is unified with our motion estimation network to simultaneously correct the motion and predict a motion-compensated denoised PET reconstruction. The experimental results on human data demonstrated that our MDPET can generate accurate motion estimation directly from low-dose gated images and produce high-quality motion-compensated low-noise reconstructions. Comparative studies with previous methods also show that our MDPET is able to generate superior motion estimation and denoising performance. Our code is available at https://github.com/bbbbbbzhou/MDPET.

Unified Retrospective EEG Motion Educated Artefact Suppression for EEG-fMRI to Suppress Magnetic Field Gradient Artefacts During Motion.

The data quality of simultaneously acquired electroencephalography and functional magnetic resonance imaging (EEG-fMRI) can be strongly affected by motion. Recent work has shown that the quality of fMRI data can be improved by using a Moiré-Phase-Tracker (MPT)-camera system for prospective motion correction. The use of the head position acquired by the MPT-camera-system has also been shown to correct motion-induced voltages, ballistocardiogram (BCG) and gradient artefact residuals separately. In this work we show the concept of an integrated framework based on the general linear model to provide a unified motion informed model of in-MRI artefacts. This model (retrospective EEG motion educated gradient artefact suppression, REEG-MEGAS) is capable of correcting voltage-induced, BCG and gradient artefact residuals of EEG data acquired simultaneously with prospective motion corrected fMRI. In our results, we have verified that applying REEG-MEGAS correction to EEG data acquired during subject motion improves the data quality in terms of motion induced voltages and also GA residuals in comparison to standard Artefact Averaging Subtraction and Retrospective EEG Motion Artefact Suppression. Besides that, we provide preliminary evidence that although adding more regressors to a model may slightly affect the power of physiological signals such as the alpha-rhythm, its application may increase the overall quality of a dataset, particularly when strongly affected by motion. This was verified by analysing the EEG traces, power spectra density and the topographic distribution from two healthy subjects. We also have verified that the correction by REEG-MEGAS improves higher frequency artefact correction by decreasing the power of Gradient Artefact harmonics. Our method showed promising results for decreasing the power of artefacts for frequencies up to 250Hz. Additionally, REEG-MEGAS is a hybrid framework that can be implemented for real time prospective motion correction of EEG and fMRI data. Among other EEG-fMRI applications, the approach described here may benefit applications such as EEG-fMRI neurofeedback and brain computer interface, which strongly rely on the prospective acquisition and application of motion artefact removal.

Binary-Like Topology Optimization of Piezoelectric Metamaterial Plate with Interface Circuits Using Extended Plane Wave Expansion Method

Piezoelectric metamaterial plate (PMP) is being investigated for structural vibration energy harvesting (SVEH), in which an interface circuit is often used. Thus, it is a challenge to perform bandgap optimization of such an elastic–electro–mechanical coupling system. This paper presents a binary-like topology optimization scheme by dividing the unit cell into identical pieces, where a {0, 1} matrix is optimized to indicate material distribution. Firstly, a unified motion equation is derived for the elastic plate and the piezoelectric patch, and an electromechanical coupling model is built for a self-powered synchronized charge extraction circuit. Then, an extended plane wave expansion method is presented to model the bandgap character of the PMP with interface circuits (PMPICs), and the numerical solution of the dispersion curves is derived based on the Bloch theorem. Next, an extended genetic algorithm is applied for the topology optimization of the PMPIC. In the end, numerical and finite element simulations are performed to validate the proposed method. The results demonstrate that both the structure and the circuit can be optimized simultaneously to obtain the maximum first-order bandgap at a given central frequency. Therefore, the proposed method should provide an effective solution for the topology optimization of a PMPIC for broadband SVEH.

Three-Dimensional Unified Motion Control of a Robotic Standing Wheelchair for Rehabilitation Purposes.

Technological advances in recent years have shown interest in the development of robots in the medical field. The integration of robotic systems in areas of assistance and rehabilitation improves the user’s quality of life. In this context, this article presents a proposal for the unified control of a robotic standing wheelchair. Considering primary and secondary tasks as control objectives, the system performs tasks autonomously and the change of position and orientation can be performed at any time. The development of the control scheme was divided in two parts: (i) kinematic controller to solve the desired motion problem; and (ii) dynamic compensation of the standing wheelchair–human system. The design of the two controllers considers the theory of linear algebra, proposing a low computational cost and an asymptotically stable algorithm, without disturbances. The stability and robustness analysis of the system is performed by analyzing the evolution of the control errors in each sampling period. Finally, real experiments of the performance of the developed controller are performed using a built and instrumented standing wheelchair.

The Operational Space Formulation on Humanoids Considering Joint Stiffness and Bandwidth Limit

As the applications of robots increase, mobility and capability of interaction in unstructured environments have become important. Hence, humanoid robots have been developed to have these capabilities, and recently, compliant motions for safe contact have been studied. The Operational Space Formulation can be an effective method for humanoid robots to realize compliant motion via unified motion and force control. Nevertheless, the implementation of the Operational Space Formulation on humanoid robots has not been successful. One of the challenging issues is low position tracking performance. In this study, a control method for solving this problem is proposed by considering the joint stiffness and joint bandwidth limits. To consider joint stiffness, the Operational Space Formulation was derived using flexible joint robot dynamics. Additionally, an extra torque generation method, which penalizes low performance actuators, is utilized to account for the bandwidth limits. Neither methods requires additional sensors or joint space controllers. Hence, they can be useful for conventional humanoid robots composed of electric motors and gears. By integrating the two methods, the position tracking performance of the Operational Space Formulation on the humanoid robot was significantly improved. The proposed method was demonstrated via position and orientation control experiments using our humanoid robot, TOCABI.

Unified theory of electroseparations

Linear electroseparations in vacuum, gas phase and liquid phase have created mass spectrometry, ion mobility spectrometry, electrophoresis and capillary electrophoresis. However, they have not systematized yet, developing independently, with their own theory, not related to each other. In this paper, unified motion equations were derived from the second law of Newtonian mechanics combined with electrostatic theory. From them, the general sub-equations of motion and measurement modes of all the above-mentioned methods were deduced and discussed briefly. These equations are not only helpful to systematize these existing methods but also are usable to deduce and discover novel electro-separation modes.

Motion Planning and Control with Randomized Payloads on Real Robot Using Deep Reinforcement Learning

In this study, a unified motion planner with low level controller for continuous control of a differential drive mobile robot under variable payload values is presented. The deep reinforcement agent takes 11-dimensional state vector as input and calculates each wheel’s torque value as a 2-dimensional output vector. These torque values are fed into the dynamic model of the robot, and lastly steering commands are gathered. In previous studies, intersection navigation solutions that uses deep-RL methods, have not been considered with variable payloads. This study is focused specifically on service robotic applications where payload is subject to change. In this study, deep-RL-based motion planning is performed by considering both kinematic and dynamic constraints. According to the simulations in a dynamic environment, the agent successfully navigates to target with 98.2% success rate in test time with unseen payload masses during training. Another agent is also trained without payload randomization for comparison. Results show that our agent outperforms the other agent, that is not aware of its own payload, with more than 40% gap. Our agent is also compared with the Time-to-Collision (TTC) algorithm. It is observed that our agent uses far less time than TTC to accomplish the mission while success rates of two methods are same. Lastly, the proposed method is applied on a real robot in order to show the real-time applicability of the approach.