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Abstract: Pneumatically driven soft actuators have been widely used in soft material robotics. However, soft pneumatic actuators are usually tethered to a rigid pump or compressor, which is complicated, cumbersome and noisy. In this study, we present a novel self-pumping actuation module which is composed of a soft origami pump, two soft pneumatic actuators, a servo motor, a controller and battery. During a working cycle, the soft pump is compressed or restored by pulling or releasing the tendons using the servo motor. As a consequence, the pneumatic actuators connected to the pump generate bending and restoring deformations. Moreover, the air flow inside the proposed module is closed-loop without exchanging air with the environment, making it possible to operation in certain scenarios such as in underwater or vacuum conditions, the advantage of our designed self-pumping actuation module is to recycle air without relying on a large rigid air pump. Theoretical model of the self-pumping actuation module is derived and its performance is characterized via several experiments. The maximum bending speed by the soft actuator is 239.2° s−1, the maximum compression speed of origami pump is 38.2 mm s−1, the maximum pressure inside the pump is 48 kPa, the maximum internal flow rate of pump is 11.5 L min−1, and the maximum torque of actuator is 0.0455 N·m. A soft robotic gripper, a fully untethered quadrupedal soft swimming robot and a rehabilitation glove are fabricated to show the superiority of the proposed design over traditional pneumatically actuated soft robots. PubDate: 2023-06-01
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Abstract: Cyber-physical systems are taking on a permanent role in the industry, such as in oil and gas or mining. These systems are expected to perform increasingly autonomous tasks in complex settings removing human operators from remote and potentially hazardous environments. High autonomy necessitates a more extensive use of artificial intelligence methods, such as anomaly detection, to identify unusual occurrences in the monitored environment. The absence of data characterizing potentially hazardous events leads to disruptive noise displayed as false alarms, a common anomaly detection issue for hazard identification applications. Contrastingly, disregarding the false alarms can result in the opposite effect, causing loss of early indications of hazardous occurrences. Existing research introduces simulating and extrapolating less represented data to expand the information on hazards and semi-supervise the methods or by introducing thresholds and rule-based methods to balance noise and meaningful information, necessitating intensive computing resources. This research proposes a novel Warning Identification Framework that evaluates risk analysis objectives and applies them to discern between true and false warnings identified by anomaly detection. We demonstrate the results by analyzing three seismic hazard assessment methods for identifying seismic tremors and comparing the outcomes to anomalies found using the unsupervised anomaly detection method. The demonstrated approach shows great potential in enhancing the reliability and transparency of anomaly detection outcomes and, thus, supporting the operational decision-making process of a cyber-physical system. PubDate: 2023-06-01
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Abstract: Swarm robotic systems comprising members with limited onboard localization capabilities rely on employing collaborative motion-control strategies to successfully carry out multi-task missions. Such strategies impose constraints on the trajectories of the swarm and require the swarm to be divided into worker robots that accomplish the tasks at hand, and support robots that facilitate the movement of the worker robots. The consideration of the constraints imposed by these strategies is essential for optimal mission-planning. Existing works have focused on swarms that use leader-based collaborative motion-control strategies for mission execution and are divided into worker and support robots prior to mission-planning. These works optimize the plan of the worker robots and, then, use a rule-based approach to select the plan of the support robots for movement facilitation – resulting in a sub-optimal plan for the swarm. Herein, we present a mission-planning methodology that concurrently optimizes the plan of the worker and support robots by dividing the mission-planning problem into five stages: division-of-labor, task-allocation of worker robots, worker robot path-planning, movement-concurrency, and movement-allocation. The proposed methodology concurrently searches for the optimal value of the variables of all stages. The proposed methodology is novel as it (1) incorporates the division-of-labor of the swarm into worker and support robots into the mission-planning problem, (2) plans the paths of the swarm robots to allow for concurrent facilitation of multiple independent worker robot group movements, and (3) is applicable to any collaborative swarm motion-control strategy that utilizes support robots. A unique pre-implementation estimator, for determining the possible improvement in mission execution performance that can achieved through the proposed methodology was also developed to allow the user to justify the additional computational resources required by it. The estimator uses a machine learning model and estimates this improvement based on the parameters of the mission at hand. Extensive simulated experiments showed that the proposed concurrent methodology improves the mission execution performance of the swarm by almost 40% compared to the competing sequential methodology that optimizes the plan of the worker robots first and, then, the plan of the support robots. The developed pre-implementation estimator was shown to achieve an estimation error of less than 5%. PubDate: 2023-05-30
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Abstract: Wheeled mobile robots, particularly omnidirectional wheeled mobile robots are widely employed for various applications in different environments, which might be subjected to unevenness and irregularities in practice. This type of robot must be able to fulfill its maneuvers kinematically to prevent disruptions due to unevenness in its navigation, still travelling desired paths. In this research, the motion of the mobile robot on uneven surfaces is investigated and its kinematic equations are revised to take the unevenness of surfaces into account, and its navigation and path tracking are studied. In this regard, the solution of real time updating the rotation matrix on the basis of Euler angles is proposed. To verify this algorithm, a procedure for obtaining Euler angles in the simulation is also presented and verified. In the experimental test, the Euler angles are calculated with the low-cost inertial sensors. Experimental tests are performed by an omnidirectional three-wheeled mobile robot on a laboratory uneven terrain specifically designed and built for this purpose. By employing this algorithm in the simulation, the positioning error caused by the unevenness of the surface was completely eliminated and the traveled path was matched with the desired path. In the experimental test, the improvement of the error of the path final point, was more than 83% and the improvement of the RMS error of all the points of the path was more than 77%. PubDate: 2023-05-25
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Abstract: Reconfigurable architecture refers to buildings whose shape can be adjusted. Such buildings exhibit potential advantages compared to traditional fixed–shape ones, including better energy efficiency and improved comfort for the occupants. A family of planar linkage mechanisms is presented to establish a framework for reconfigurable buildings. These mechanisms constitute the basic structural and reconfiguration elements of the proposed building concept. They are kinematically coupled versions of well–known planar mechanisms, namely the 4–bar, the crank–slider, the swinging–block, and the turning–block. A control procedure, which involves alternative multistep reconfiguration sequences becomes relevant. It allows for energy efficient reconfigurations, while providing flexibility in motion planning. Simulation studies together with laboratory–scale hardware implementations exemplify the concepts, demonstrate the applicability of the methods, and highlight the potential as well as the challenges of reconfigurable architecture. Its relevance to robotics also becomes apparent. PubDate: 2023-05-25
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Abstract: The use of spherical robots in outdoor operations has increased because they can move on uneven/three-dimensional (3D) terrain. Since the non-holonomic constraints and the rolling, tilting and turning kinematics of spherical robots are coupled on 3D terrain, these operations may require complex design or advanced control techniques for stable rolling kinematics on a straight trajectory. Instead, a simple design or solution can be used for these operations. This study proposes a simple design for stable rolling kinematics of spherical robots on a straight path without changing the existing design and without a controller. The proposed design is based on coupling the spherical robots with a mechanical component and can be easily applied to all spherical robots. The proposed design does not require any change in the structure of a spherical robot, but only an additional identical spherical robot and a mechanical coupler. The main contribution and significance of this study is a simple design to overcome the stability problems of a single spherical robot operating on flat and 3D terrain. The rolling stability of the single and the coupled spherical robots on flat road and 3D terrain was investigated by kinematic analysis to verify the validity of the proposed design. The effect of the stiffness of the mechanical coupling on the rolling kinematics of the spherical robots was studied in the kinematic analysis using different mechanical couplings, such as a rigid shaft, a relatively soft spring and a relatively stiff spring. Experimental studies were conducted to verify the validity of the proposed design for the spherical robots rolling especially on 3D terrains. The results show that the proposed design, which requires only a mechanical coupler instead of a complex design or advanced controller, is reliable and feasible. The rigid mechanical coupling of the two identical spherical robots could overcome the problems of maneuvering and rolling stability of spherical robots on 3D terrains. PubDate: 2023-05-25
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Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Abstract: In the growing field of study known as “soft robotics,“ highly adaptable robots are built for soft interactions by utilizing the acquiescence, and flexibility of soft structures. The substantial advancement of soft grippers may be attributed to the growth of soft robotics, the investigation of various materials, and the creation of flexible electronics. The field of soft robotics does have the potential to have a substantial influence, among other applications, on the field of soft grippers and manipulators. Grippers of various varieties are necessary for handling various types of items, both hard and soft. It is crucial to adopt flexible and adaptive gripping tactics to get more item holding flexibility. Soft-robotic grasping systems that are extremely flexible in terms of workpiece shape, size, and structure are an ideal choice for increasing production flexibility. The major reason for the review is to learn about the existing soft gripper and the repeatability of existing soft-robotic grippers with large payload capacities. This article offers a thorough analysis of soft gripper recommendations, covering machine learning techniques along with physical theories, sensor technologies, actuation strategies, and device topologies. The potential effects of a soft robot manipulator for industry and the social economy are discussed as this essay comes to a close. PubDate: 2023-05-18
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Abstract: Flexible robots have exhibited impressive features in working in congested environments due to their compliance behavior and morphological structure. However, designing motion planning techniques and robust control strategies that actively control their deformations are challenging in many applications. Thus, this article presents the learning by Demonstration (LbD) approach for planning the spatial point-to-point motions of a multi-section continuum robot. Via teleoperation, the human demonstrations are captured by moving the flexible interface with similar kinematics of the active robot in front of the Motion Capture System (MCS). Meanwhile, a Nonlinear Model Predictive Control (NMPC) scheme is proposed based on the robot’s kinematic model to follow the reference trajectories while respecting the constraints imposed by the cable lengths and control actions. The simulation results prove the efficiency of the LbD approach in reproducing and generalizing the spatial motions of the robot’s tip and avoiding obstacles and external disturbances. On the other hand, the numerical simulations show the performance of NMPC scheme in terms of trajectory tracking and avoiding static and dynamic obstacles. Additionally, its robustness is analyzed by comparing it to the Pseudo-Inverse Jacobian Kinematic Control (PIJKC) while considering the constraints of cable lengths. Finally, the stability of NMPC is evaluated against input perturbations using the Monte Carlo simulations. PubDate: 2023-05-17
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Abstract: Dynamics simulation is an important technique for hexapod robots. However, the realistic locomotion of a robot is comprehensive due to kinematics error, mechanism deformation, sinkage, slippage, and dragging of the feet on the ground. To investigate this phenomenon, this paper presents a kinematics and dynamics model of a hexapod robot to include this effect in dynamics simulation. The compliance of both the robot and terrain are taken into consideration. The total compliance matrix and compatibility equation are established with the consideration of the compliance of the legs, body, and terrain. The body of the robot is modeled to have a coupled compliance to consider the effect of all six legs. The theory of terramechanics is introduced to describe the constraint between the feet of the robot and terrain. The complete dynamics model of hexapodal walking is built on the foundation of the compliant kinematics model and foot-terrain interaction mechanics model. Numerical simulation and experiments are performed based on a bio-inspired hexapod robot. The simulation and experimental results indicate that the model can provide a reliable accuracy with only analytical and a priori data as inputs. PubDate: 2023-05-16
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Abstract: Wheeled locomotion mechanisms can traverse even terrains with high velocity, while tracked locomotion mechanisms can traverse rough terrains. Since different locomotion mechanisms are suitable for different terrains, there has always been a problem to choose appropriate modes according to terrains for all-terrain unmanned ground vehicles (UGVs). In order to make UGVs can traverse various terrains efficiently, based on the concept of mechanism reconfiguration, the reconfigurable deformable tracked wheel (RDTW) is proposed, which can realize wheeled mode and tracked mode. The mechanical design of RDTW is introduced, and the kinematic of reconfigurable rims is investigated. The nonlinear terramechanics model is established by coupling with the deformation parameter of reconfigurable mechanisms. Further, this model is validated by Multibody Dynamics-Discrete Element Method (MBD-DEM) co-simulation and experiments. Based on the theoretical model, the passing ability can be improved by changing the configuration of the mechanism. The simulation and test prove that the structural design of RDTW is reasonable and effective, and the optimal deformation strategy obtained from the terramechanics based on its structure is effective and can be applied in practice. The analysis results show that the nonlinear sinkage curves and traction performance of UGVs can be effectively improved by configuring RDTW. The proposed locomotion mechanism is an important attempt in improving the design of multi-locomotion-mode UGVs. PubDate: 2023-05-11
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Abstract: The Adaptive Monte Carlo Localization (AMCL) is a common technique for mobile robot localization problem. However, AMCL performs poorly on localization when robot navigates to a featureless environment. To address this issue, an enhanced AMCL is proposed through using the information from laser scan points to improve the preciseness and robustness of the localization problem for service robots. The proposed new method first matches the laser scan points with a pre-built grid map by an iterative closest point (ICP) algorithm and then designs a Localization Confidence Estimation (LCE) method to evaluate the localization credibility of ICP and AMCL respectively. Finally, the ICPs with high LCE scores are selected to inject particle swarms in the form of particles with adaptive amounts to optimize the next step of the AMCL estimation process. With the improved method, AMCL’s particle swarm can quickly converge to the correct position after several iterations. Experimental results show that the proposed algorithm outperforms the original AMCL in respect of accuracy and robustness even in dynamic environments. PubDate: 2023-05-09
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Abstract: A haptic device (HD) is an interface used for simulating a virtual environment (VE) for its operator. While simulating a VE, the HD should be stable; otherwise, it can damage itself or its operator. Usually, HDs are multi-degree-of-freedom serial manipulators with sensor quantization and friction in their joints. Hence, the HD dynamics is complex and its analytical stability analysis is complicated. During simulating of the VE for the operator, stylus movements are small. In the previous studies, the multi-DOF nonlinear dynamics of the HD was replaced with simple dynamics in which mass and viscous values are constant. However, there were neither analytical methods to determine the values of the mentioned parameters in the simplified model nor studying the accuracy of this simplification is studied. In this paper, a novel and general approach is employed for simplifying a multi-degree-of-freedom haptic device dynamics during arbitrary motion around the operating point, and its accuracy in the prediction of the stable simulation of the VE is discussed. Meanwhile, sensor quantization and Coulomb friction are considered in the model. This method is evaluated through simulation for stability analysis of the PHANToM 1.5 and KUKA Light Weight Robot IV (LWR IV) as haptic interfaces in various situations. PubDate: 2023-05-08
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Abstract: Focusing on the problem of extracting a set of feasible parameters to characterize the standard Newton-Euler (SN-E) dynamics model of robots, as an alternative to the linear matrix inequalities framework, a composite multiobjective differential evolution (MODE) algorithm based on the constraints of the linear combination vector inferred from the dynamic variables and the physical characteristics of the rigid links is proposed to recover feasible parameters from the estimated set of basic inertial parameters. In order to solve the challenge of difficult population evolution caused by complex feasible regions, the trial vector generation strategy for convergence is implemented through the elaborately combination of feasibility rule and \(\varepsilon \) constrained method. In addition, the peak deviation of prediction of the classical viscous-coulomb (Vis-Cou) friction model during the robot joint inversion has thus far remained an open question, which is addressed by a specially developed improved model based on the viscous-arctan function. The proposed solutions have been validated with a set of experiments on a six degree-of-freedom (DOF) robot. The experiment results show that the established SN-E model tracks the actual torque effectively, and compared with the classical friction model, the optimized model reduces the deviation of the predicted torque by 22.1% while the peak error is effectively eliminated. PubDate: 2023-05-08
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Abstract: Hydraulic driven legged robots have the advantage of large load capacity and strong environmental adaptability, which has a wide range of prospects for military and civilian applications. And its joint is driven by hydraulic actuator, which is structured as a valve-controlled cylinder and is called hydraulic drive unit (HDU). The control accuracy of the HDU affects the control performance of the robot. And it is difficult for a single control method to meet the requirements of high accuracy control of robot joints. Therefore, in order to meet the requirements for high-accuracy periodic gait of legged robots, an impedance compound control of the HDU is designed based on the authors' previous research of state feedback control (SFC). Firstly, according to the characteristics of the periodic signal, the system error is analyzed, and plug-in repetitive control (PIRC) is designed. Secondly, considering the influence of load force on control accuracy, a model-based feedforward disturbance rejection control (FDRC) is designed. Finally, a high-accuracy impedance compound control of the HDU combined the SFC, PIRC and FDRC is formed and the control structure is also designed. The experimental results show that both PIRC and FDRC can improve the control accuracy of the HDU, and PIRC has better control effect. The reduction rates of the maximum error and mean square error are all more than 80%. PubDate: 2023-05-04
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Abstract: Currently, several platforms offer solutions for the management and control of fleets of unmanned aerial vehicles (UAVs), addressing a wide range of scenarios, each with its own particular set of objectives. Some of these solutions are mission planning platforms for broader usage, without aiming to solve a single scenario. However, these often either do not support multi-UAV collaboration or generate a static flight trajectory, which does not facilitate the coordination of a fleet of several UAVs in a mission that may need to adapt to the current environment. Through the development of a domain-specific language (DSL) - EasyMission - for UAV mission definition and control, we introduce a mission planning framework that makes it possible to describe mission plans that also enable the user to define adjustments and constraints that may have to be taken into account in real-time according to sensor readings or other events. This framework enables inexperienced users to design missions with low or moderate complexity levels, while still being a useful tool for advanced users due to its versatility in addressing multiple scenarios through a single platform. We show how the mission framework is able to easily define differentiated mission examples with distinct purposes and scenarios, and with real-time decisions and constraints. PubDate: 2023-05-02
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Abstract: Due to their inherent deformability, controlling continuum robots (CRs) comes with many challenges, including strong nonlinearity, uncertainty, and disturbance. In this paper, a planar CR is modeled as a general multi-input multi-output (MIMO) system with internal uncertainty and external disturbance. To improve the trajectory tracking performance, an active disturbance rejection control (ADRC)-based control strategy for the CR is proposed. The proposed method can regard the internal uncertainty and external disturbance of the CR as an overall disturbance. In the ADRC framework, a linear extended state observer (ESO) is designed to timely estimate the overall disturbance, and a closed-loop control with disturbance compensation and feedback control law is implemented. The convergence of the designed ESO and the stability of the ADRC-based controller are studied. Simulations and experiments are performed to verify the effectiveness of the proposed approach. PubDate: 2023-04-27
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Abstract: Autonomous driving technology is safety-critical and thus requires thorough validation. In particular, the probabilistic algorithms employed in perception systems of autonomous vehicles (AV) are notoriously hard to validate due to the wide range of possible critical scenarios. Such critical scenarios cannot be easily addressed with current manual validation methods, thus there is a need for an automatic and formal validation technique. To this end, we propose a new approach for perception component verification that, given a high-level and human-interpretable description of a critical situation, generates relevant AV scenarios and uses them for automatic verification. To achieve this goal, we integrate two recently proposed methods for the generation and the verification that are based on formal verification tools. First, we use formal conformance test generation tools to derive, from a verified formal model, sets of scenarios to be run in a simulator. Second, we model check the traces of the simulation runs to validate the probabilistic estimation of collision risks. Using formal methods brings the combined advantages of an increased confidence in the correct representation of the chosen configuration (temporal logic verification), a guarantee of the coverage and relevance of automatically generated scenarios (conformance testing), and an automatic quantitative analysis of the test execution (verification and statistical analysis on traces). PubDate: 2023-04-21
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Abstract: In collaborative robotics the manipulator trajectory has to be planned to avoid collisions, yet in real-time. In this paper we pose the problem as minimization of a quadratic functional among piecewise linear trajectories in the angular (joint) space. The minimization is subjected to novel nonlinear inequality constraints that simplify the original non-penetration constraints to become cheap to evaluate in real time while still preserving collision-avoidance. The very first and most critical step of the computation is to find an initial trajectory that is free of collisions. To that goal we minimize a weighted sum of the violated constraints until they become feasible or a maximal number of steps is reached. Sometimes an incremental growing of the obstacle helps. By incremental growing we mean that we sequentially solve auxiliary subproblems with obstacles growing from ground or falling from top and use as the initial trajectory the one optimized in the previous step. The initial trajectory is then optimized while preserving feasibility at each step. We solve a sequence of simple-bound constrained quadratic programming problems formulated in the dual space of Lagrange multipliers, which are related to the original linearized inequality constraints that are active or close-to-active. Finally, we refine the trajectory parameterization and repeat the optimization, which we refer to as an hierarchical approach, until an overall prescribed time limit, being well below a second, is reached. PubDate: 2023-04-21
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