Boolean networks, as logical dynamical systems where the system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. In this paper, we present a framework to ev...
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Boolean networks, as logical dynamical systems where the system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. In this paper, we present a framework to evaluate whether and how the closed-loop dynamics of a controlled Boolean network can be shaped into any prescribed form by state-feedback control. We refer to this problem as to the feedback shaping for Boolean networks. First of all, based on the linear representation of Boolean networks, we establish a necessary and sufficient rank condition for a controlled Boolean network to be feedback shapable or not. Next, we design an algorithm for the synthesis of closed-loop dynamics for a feedback shapable Boolean network, such that for any given controlled Boolean network and a desired closed-loop dynamics, one can always find a feedback control law so that the closed-loop dynamics is precisely realized.
Occupancy mapping has been widely utilized to represent the surroundings for autonomous robots to perform tasks such as navigation and manipulation. While occupancy mapping in 2-D environments has been well-studied, t...
Occupancy mapping has been widely utilized to represent the surroundings for autonomous robots to perform tasks such as navigation and manipulation. While occupancy mapping in 2-D environments has been well-studied, there have been few approaches suitable for 3-D dynamic occupancy mapping which is essential for aerial robots. This paper presents a novel 3-D dynamic occupancy mapping algorithm called DS-K3DOM. We first establish a Bayesian method to sequentially update occupancy maps for a stream of measurements based on the random finite set theory. Then, we approximate it with particles in the Dempster-Shafer domain to enable real-time computation. Moreover, the algorithm applies kernel-based inference with Dirichlet basic belief assignment to enable dense mapping from sparse measurements. The efficacy of the proposed algorithm is demonstrated through simulations and real experiments i i The code is available at: https://***/JuyeopHan/dsk3dom_public.
Automatic Guided Vehicle (AGV) has been widely used in the warehouse for transporting the bulky and heavy cargos. However, the AGV may deviate the regular trajectories in presence of incorrect or untimely commands sen...
Automatic Guided Vehicle (AGV) has been widely used in the warehouse for transporting the bulky and heavy cargos. However, the AGV may deviate the regular trajectories in presence of incorrect or untimely commands sent form the server due to, e.g., cyber attacks, unexpected blocks of the wireless signals. In order to ensure AGV running safely, this paper presents a visual surveillance system by making full use of the measurements from the forward and downward cameras. Specifically, the forward camera estimates the AGV positions and attitudes by tracking the surrounding landmarks detected from the forward image sequences. Besides, the downward camera is used to detect the QR codes fixed on the floor and estimate the AGV poses in the absolute reference frame. Apart from that, the AGV poses from the downward camera could correct scale and poses estimated the forward view. The proposed method has been extensively performed on the developed platform. The results proves the effectiveness in using the complementary forward-downward visual measurements for AGV security surveillance.
Boolean networks, as logical dynamical systems whose system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. The representation and control of Boolean netwo...
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Boolean networks, as logical dynamical systems whose system states are Boolean variables, arise from applications in biology, computer networks, and social networks etc. The representation and control of Boolean networks have attracted a lot of attention in recent years. On a parallel line of research, Koopman developed an operator view of nonlinear dynamical systems in early 1930s, which shows that using observable functions all nonlinear dynamics can be represented as (infinite dimensional) linear systems. In this paper, we present a framework for representing Boolean networks via Koopman approach. First of all, we construct addition and scalar multiplication operations over the set of logical functions over the binary field, defining a linear Boolean function space. Then associated with any Boolean mapping, the induced Koopman operator is defined as an operator over such Boolean function space. Next, we show that if there exists a set of logical functions that are invariant in the Koopman sense, a Boolean network can be represented by a finite-dimensional linear system. This Koopman perspective for Boolean networks is also extended to controlled Boolean networks.
This paper presents a navigation solution for a vehicle operating in cooperation with two other. The vehicle is assumed to measure bearing to one of the aiding vehicles and range to the other. An observer with globall...
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This paper presents a navigation solution for a vehicle operating in cooperation with two other. The vehicle is assumed to measure bearing to one of the aiding vehicles and range to the other. An observer with globally exponentially stable error dynamics is designed by obtaining an equivalent observable linear time-varying system using an artificial output and state augmentation. The observer relies on local measurements, as well as limited communication between the vehicles. Simulations are performed to assess the proposed solution.
Microrobot has been developed for the manipulation of micro- and nanoscale objects for many biological and manufacturing tasks. However, there are still challenges in the collision-free operation of microrobots in mul...
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ISBN:
(纸本)9781665481106
Microrobot has been developed for the manipulation of micro- and nanoscale objects for many biological and manufacturing tasks. However, there are still challenges in the collision-free operation of microrobots in multiple scenarios. Essential functions, such as path planning and autonomous and adaptive navigation in dynamic environments, are urgently needed to implement microrobots in practical scenarios. Here, we implement path planning and the autonomous navigation of microrobots in 2D static obstacle scenarios and micro-mazes. A probabilistic-based RRT algorithm is employed to speed up the path search in static obstacle scenarios. The Dijkstra algorithm is employed in the micro-maze navigation of the microrobot to avoid the narrow and long pipeline effect. To further ease the active manipulation of magnetic mobile microrobots, a handle-based interactive operation is developed to realize the operational tasks in the three-dimensional space based on artificial vision planning and navigation, which improves the interactivity and flexibility of the system, and supplements the current limitation of autonomous navigation on the three-dimensional space.
Cleaning robots have been widely used in our daily life, achieving huge success in the service robot sector. The autonomous movement and decision-making of these robots directly depend on their environmental perceptio...
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ISBN:
(纸本)9781665481106
Cleaning robots have been widely used in our daily life, achieving huge success in the service robot sector. The autonomous movement and decision-making of these robots directly depend on their environmental perception capability, which is implemented using SLAM (simultaneous localization and mapping) technique. In order to achieve better environmental perception and intelligent decision-making, it is necessary to introduce visual SLAM into cleaning robot and take full advantage of visual information to achieve higher-level perception, instead of sticking to current feature point or pixel level perception capability. In this paper, we propose a framework for semantic mapping with object model replacement visualization in indoor scenes for cleaning robot. We use an EKF-based method to fuse wheel odometry and visual odometry, and build a map representation for navigation in the framework. We obtain a semantic map by fusing object detection and point cloud segmentation. We also develop object model replacement for better visualization purposes. Finally, we conduct dataset tests and real experiments to validate our proposed framework.
Autonomous Underwater Vehicle (AUV), also called autonomous underwater robot, refers to an underwater robot that can independently complete tasks such as autonomous navigation, autonomous obstacle avoidance, and auton...
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ISBN:
(纸本)9781665481106
Autonomous Underwater Vehicle (AUV), also called autonomous underwater robot, refers to an underwater robot that can independently complete tasks such as autonomous navigation, autonomous obstacle avoidance, and autonomous operation without human intervention. In some complex and narrow detection scenarios, autonomous underwater robots need to have a small volume, a high level of autonomy, and good maneuverability. Here, we design a miniature autonomous underwater robot driven by propellers, which integrates a high-performance processor, camera module, high-precision inertial measurement unit (IMU), etc. The attitude and position information of the robot is obtained in real-time through the IMU, and the processor controls the motion state of the six propellers, achieving the motion in six degrees of freedom in space. The highly integrated design ensures the maximum length of the whole machine within 15 cm, the 3-way PID controller design ensures an efficient and stable attitude control, and the high-performance processor provides more possibilities for target tracking and recognition. The developed AUV in this study shows superior navigation performance through narrow passages.
Among the rehabilitation therapies for patients with stroke or paralysis, robot-assisted rehabilitation is a research hotspot now. However, there are not many cases of clinical application, mainly because of the compl...
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Nonvolatile memories are widely used in emerging energy-harvesting Internet-of-Things (IoT) applications, and nonvolatile memories constructed from FeFET devices hold great promise. This paper presents a nonvolatile a...
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ISBN:
(数字)9798350330991
ISBN:
(纸本)9798350331004
Nonvolatile memories are widely used in emerging energy-harvesting Internet-of-Things (IoT) applications, and nonvolatile memories constructed from FeFET devices hold great promise. This paper presents a nonvolatile and single-event-upset (SEU)-recoverable latch based on FeFET and CMOS for energyharvesting devices. The latch uses n-type FeFET devices to provide nonvolatility without any additional control signals. Moreover, since the soft error problem has become increasingly severe, radiation hardening by design gains a great attention as a promising approach to mitigate the reliability issue. The latch uses feedback interlocked loops with n-type FeFETs and C-elements, enabling it to provide nonvolatility and SEU-recovery simultaneously. Simulation results with Candence Virtuoso verifies that the proposed latch design has correct functioning with excellent performance compared to the state-of-the-art designs.
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