Cooperative People Tracking by Distributed Cameras Network

In the application of video surveillance, reliable people detection and tracking are always challenging tasks. The conventional single-camera surveillance system may encounter difficulties such as narrow-angle of view and dead space. In this paper, we proposed multi-cameras network architecture with an inter-camera hand-off protocol for cooperative people tracking. We use the YOLO model to detect multiple people in the video scene and incorporate the particle swarm optimization algorithm to track the person movement. When a person leaves the area covered by a camera and enters an area covered by another camera, these cameras can exchange relevant information for uninterrupted tracking. The motion smoothness (MS) metrics is proposed for evaluating the tracking quality of multi-camera networking system. We used a three-camera system for two persons tracking in overlapping scene for experimental evaluation. Most tracking person offsets at different frames were lower than 30 pixels. Only 0.15% of the frames showed abrupt increases in offsets pixel. The experiment results reveal that our multi-camera system achieves robust, smooth tracking performance.

Research on Nonlinear Coupled Tracking Controller for Double Pendulum Gantry Cranes With Load Hoisting/lowering

Gantry cranes, which have attracted extensive attention, are mostly simplified as nonlinear single pendulum systems without load hoisting/lowering. However, in fact, due to the existence of the hook, gantry cranes produce double pendulum swing. With an extra underactuated degree of freedom, the anti-swing control of the double pendulum gantry cranes becomes more difficult than that of single pendulum gantry cranes, especially when load hoisting/lowering is considered simultaneously. Moreover, large swings, which lead to problems such as inaccurate positioning and low transportation efficiency, may be caused by double pendulum gantry cranes with load hoisting/lowering. In this paper, a nonlinear coupled tracking anti-swing controller is proposed to solve these problems. In this controller, a smooth tracking trajectory is introduced to ensure the stable start and run of the trolley, and a coupled signal is constructed to eliminate the residual swing angles of gantry crane system. The system stability is analyzed by using Lyapunov method and Barbarat theorem. Theoretical derivation, simulation and experimental results show that the proposed controller has excellent control performance, specifically, not only does it ensure accurate positioning of the load, but also it suppresses and eliminates the hook/load swing angle effectively. The proposed controller can still achieve good control effects and has strong robustness under the condition of changing the load mass, trolley target displacement, system initial swing angles and adding external disturbance.

Look where you go: characterizing eye movements toward optic flow

When we move through our environment, objects in the visual scene create optic flow patterns on the retina. Even though optic flow is ubiquitous in everyday life, it is not well understood how our eyes naturally respond to it. In small groups of human and non-human primates, optic flow triggers intuitive, uninstructed eye movements to the pattern’s focus of expansion (Knöll, Pillow & Huk, 2018). Here we investigate whether such intuitive oculomotor responses to optic flow are generalizable to a larger group of human observers, and how eye movements are affected by motion signal strength and task instructions. Observers (n = 43) viewed expanding or contracting optic flow constructed by a cloud of moving dots radiating from or converging toward a focus of expansion that could randomly shift. Results show that 84% of observers tracked the focus of expansion with their eyes without being explicitly instructed to track. Intuitive tracking was tuned to motion signal strength: saccades landed closer to the focus of expansion and smooth tracking was more accurate when dot contrast, motion coherence, and translational speed were high. Under explicit tracking instruction, the eyes aligned with the focus of expansion more closely than without instruction. Our results highlight the sensitivity of intuitive eye movements as indicators of visual motion processing in dynamic contexts.

A Lyapunov Approach to Set the Parameters of a PI-Controller to minimise Velocity Oscillations in a Permanent Magnet Synchronous Motor using Chopper Control for Electrical Vehicles

This paper deals with a parameter set up of a PI-regulator to be applied in a system for permanent magnet three-phase synchronous motors to obtain a smooth tracking dynamics even though a chopper control structure is included in the drive. High performance application of permanent magnet synchronous motors (PMSM) is increasing. In particular, application in electrical vehicles is used very much. The technique uses a geometric decoupling procedure and a Lyapunov approach to perform a PWM control to be used as a chopper. Chopper control structures are very popular because they are very cheap and easy to be realise. Nevertheless, using a chopper control structure smooth tracking dynamics could be difficult to obtain without increasing the switching frequency because of the discontinuity of the control signals. No smooth tracking dynamics lead to a not comfortable travel effect for the passengers of an electrical vehicle or, more in general, it could be difficult to generate an efficient motion planning if the tracking dynamics are not smooth. This paper presents a technique to minimise these undesired effects. The presented technique is generally applicable and could be used for other types of electrical motors, as well as for other dynamic systems with nonlinear model structure. Through simulations of a synchronous motor used in automotive applications, this paper verifies the effectiveness of the proposed method and discusses the limits of the results.

Uncalibrated Visual Servoing for Underwater Vehicle Manipulator Systems with an Eye in Hand Configuration Camera

This paper presents an uncalibrated visual servoing scheme for underwater vehicle manipulator systems (UVMSs) with an eye-in-hand camera under uncertainties. These uncertainties contain vision sensor parameters, UVMS kinematics and feature position information. At first, a linear separation approach is addressed to collect these uncertainties into vectors, and this approach can also be utilized in other free-floating based manipulator systems. Secondly, a novel nonlinear adaptive controller is proposed to achieve image error convergence by estimating these vectors, the gradient projection method is utilized to optimize the restoring moments. Thirdly, a high order disturbance observer is addressed to deal with time-varying disturbances, and the convergence of the image errors is proved under the Lyapunov theory. Finally, in order to illustrate the effectiveness of the proposed method, numerical simulations based on a 9 degrees of freedom (DOFs) UVMS with an eye-in-hand camera are conducted. In simulations, the UVMS is expected to track a circle trajectory on the image plane, meanwhile, time-varying disturbances are exerted on the system. The proposed scheme can achieve accurate and smooth tracking results during simulations.

Robust Geometric Navigation of a Quadrotor UAV on SE(3)

SUMMARYIn this paper, a robust geometric navigation algorithm, designed on the special Euclidean group SE(3), of a quadrotor is proposed. The equations of motion for the quadrotor are obtained using the Newton–Euler formulation. The geometric navigation considers a guidance frame which is designed to perform autonomous flights with a convergence to the contour of the task with small normal velocity. For this purpose, a super twisting algorithm controls the nonlinear rotational and translational dynamics as a cascade structure in order to establish the fast and yet smooth tracking with the typical robustness of sliding modes. In this sense, the controller provides robustness against parameter uncertainty, disturbances, convergence to the sliding manifold in finite time, and asymptotic convergence of the trajectory tracking. The algorithm validation is presented through experimental results showing the feasibility of the proposed approach and illustrating that the tracking errors converge asymptotically to the origin.