Visual Control Approach Research Articles

Population dynamics of Euphyllura olivina Costa, 1857 (Psyllidae: Hemiptera) in olive trees in the semi-arid region of Djelfa (Algeria)

We studied the population dynamics of the olive psyllid Euphyllura olivina Costa, 1857 in a semi-arid region (Djelfa, central Algeria) during a year, from December 2017 to November 2018. The visual control approach and the striking method were used to monitor the different stages of this pest. The species had two generations per year: a spring generation from March to June and a fall generation from September to November. The first generation of eggs is laid in March and continues through May. The second generation begins in late August and early September and continues through November. The statistical study of the impact of the researched climatic factors (minimum, maximum, and average temperatures; precipitation and frost) on the various stages differs from one stage to the next.

VR-Goggles for Robots: Real-to-Sim Domain Adaptation for Visual Control

In this letter, we deal with the reality gap from a novel perspective, targeting transferring deep reinforcement learning (DRL) policies learned in simulated environments to the real-world domain for visual control tasks. Instead of adopting the common solutions to the problem by increasing the visual fidelity of synthetic images output from simulators during the training phase, we seek to tackle the problem by translating the real-world image streams back to the synthetic domain during the deployment phase, to make the robot feel at home . We propose this as a lightweight, flexible, and efficient solution for visual control, as first, no extra transfer steps are required during the expensive training of DRL agents in simulation; second, the trained DRL agents will not be constrained to being deployable in only one specific real-world environment; and third, the policy training and the transfer operations are decoupled, and can be conducted in parallel. Besides this, we propose a simple yet effective shift loss that is agnostic to the downstream task, to constrain the consistency between subsequent frames which is important for consistent policy outputs. We validate the shift loss for artistic style transfer for videos and domain adaptation , and validate our visual control approach in indoor and outdoor robotics experiments.

Control of Redundant Joint Structures Using Image Information During the Tracking of Non-Smooth Trajectories

Visual information is increasingly being used in a great number of applications in order to perform the guidance of joint structures. This paper proposes an image-based controller which allows the joint structure guidance when its number of degrees of freedom is greater than the required for the developed task. In this case, the controller solves the redundancy combining two different tasks: the primary task allows the correct guidance using image information, and the secondary task determines the most adequate joint structure posture solving the possible joint redundancy regarding the performed task in the image space. The method proposed to guide the joint structure also employs a smoothing Kalman filter not only to determine the moment when abrupt changes occur in the tracked trajectory, but also to estimate and compensate these changes using the proposed filter. Furthermore, a direct visual control approach is proposed which integrates the visual information provided by this smoothing Kalman filter. This last aspect permits the correct tracking when noisy measurements are obtained. All the contributions are integrated in an application which requires the tracking of the faces of Asperger children.

Sinusoidal input-based visual control for nonholonomic vehicles

SUMMARYThis paper proposes a new visual control approach based on sinusoidal inputs to be used on a nonholonomic robot. We present several contributions: In our method, developed considering a unicycle kinematic model, sinusoids are used in such a way that the generated vehicle trajectories are feasible, smooth and versatile. Our technique improves previous sinusoidal-based control works in terms of efficiency and flexibility. As further contributions, we present analytical expressions for the evolution of the robot's state, and propose a new state-feedback control law based on these expressions. All the information used in the control scheme is obtained from omnidirectional vision by means of the one-dimensional trifocal tensor. Stability analysis of the proposed approach is presented, and its performance is illustrated through experiments.

Switching visual control based on epipoles for mobile robots

In this paper, we present a visual control approach consisting in a switching control scheme based on the epipolar geometry. The method facilitates a classical teach-by-showing approach where a reference image is used to control the robot to the desired pose (position and orientation). As a result of our proposal a mobile robot carries out a smooth trajectory towards the target and the epipolar geometry model is used through the whole motion. The control scheme developed considers the motion constraints of the mobile platform in a framework based on the epipolar geometry that does not rely on artificial markers or specific models of the environment. The proposed method is designed in order to cope with the degenerate estimation case of the epipolar geometry with short baseline. Experimental evaluation has been performed in realistic indoor and outdoor settings.