Potential problems and switching control for visual servoing

This paper proposes a potential switching scheme that enlarges the stable region of feature-based visual servoing. Relay images that interpolate initial and reference image features are generated by using affine transformation. Artificial potentials defined by the relay images are patched around the reference point of the original potential to enlarge the stable region. Simulations with simplified configuration and experiments on a 6 DOF robot show the validity of the proposed control scheme</p

Visual servoing of a car-like vehicle - an application of omnidirectional vision

In this paper, we develop the switching controller presented by Lee et al. for the pose control of a car-like vehicle, to allow the use of an omnidirectional vision sensor. To this end we incorporate an extension to a hypothesis on the navigation behaviour of the desert ant, cataglyphis bicolor, which leads to a correspondence free landmark based vision technique. The method we present allows positioning to a learnt location based on feature bearing angle and range discrepancies between the robot's current view of the environment, and that at a learnt location. We present simulations and experimental results, the latter obtained using our outdoor mobile platform

Technical report on Optimization-Based Bearing-Only Visual Homing with Applications to a 2-D Unicycle Model

We consider the problem of bearing-based visual homing: Given a mobile robot which can measure bearing directions with respect to known landmarks, the goal is to guide the robot toward a desired "home" location. We propose a control law based on the gradient field of a Lyapunov function, and give sufficient conditions for global convergence. We show that the well-known Average Landmark Vector method (for which no convergence proof was known) can be obtained as a particular case of our framework. We then derive a sliding mode control law for a unicycle model which follows this gradient field. Both controllers do not depend on range information. Finally, we also show how our framework can be used to characterize the sensitivity of a home location with respect to noise in the specified bearings. This is an extended version of the conference paper [1].Comment: This is an extender version of R. Tron and K. Daniilidis, "An optimization approach to bearing-only visual homing with applications to a 2-D unicycle model," in IEEE International Conference on Robotics and Automation, 2014, containing additional proof

Robot eye-hand coordination learning by watching human demonstrations: a task function approximation approach

We present a robot eye-hand coordination learning method that can directly learn visual task specification by watching human demonstrations. Task specification is represented as a task function, which is learned using inverse reinforcement learning(IRL) by inferring differential rewards between state changes. The learned task function is then used as continuous feedbacks in an uncalibrated visual servoing(UVS) controller designed for the execution phase. Our proposed method can directly learn from raw videos, which removes the need for hand-engineered task specification. It can also provide task interpretability by directly approximating the task function. Besides, benefiting from the use of a traditional UVS controller, our training process is efficient and the learned policy is independent from a particular robot platform. Various experiments were designed to show that, for a certain DOF task, our method can adapt to task/environment variances in target positions, backgrounds, illuminations, and occlusions without prior retraining.Comment: Accepted in ICRA 201

Air vehicle simulator: an application for a cable array robot

The development of autonomous air vehicles can be an expensive research pursuit. To alleviate some of the financial burden of this process, we have constructed a system consisting of four winches each attached to a central pod (the simulated air vehicle) via cables - a cable-array robot. The system is capable of precisely controlling the three dimensional position of the pod allowing effective testing of sensing and control strategies before experimentation on a free-flying vehicle. In this paper, we present a brief overview of the system and provide a practical control strategy for such a system. ©2005 IEEE

Potential switching control in visual servo

Stability of feature-based visual servoing controllers proposed so far is local. The initial features far from the reference may converge to features different from the reference or, even worse, they may not converge. In this paper, the stability of feature-based visual servoing is considered by using potential. The stable region is visualized and artificial potential switching is proposed to extend the stable region</p

A comparative study on the performance of neural networks in visual guidance and feedback applications

Vision-based systems increase the flexibility of industrial automation applications by providing non-touching sensory information for processing and feedback. Artificial neural networks (ANNs) help such conformities through prediction in overcoming nonlinear computational spaces. They transform multiple possibilities of outcomes or regions of uncertainty posed by the system components towards solution spaces. Trained networks impart a certain level of intelligence to robotic systems. This paper discusses two applications of machine vision. The 3 degrees of freedom (DOF) robotic assembly provides an accurate cutting of soft materials with visual guidance using pixel elimination. The 6-DOF robot combines visual guidance from a supervisory camera and visual feedback from an attached camera. Using a switching approach in the control strategy, pick and place applications are carried out. With the inclusion of ANN to make the strategies intelligent, both the systems performed better with regard to computational time and convergence. The networks make use of the extracted image features from the scene for different applications. Simulation and experimental results validate the proposed schemes and show the effectiveness of ANN in machine vision applications

Multi-Focal Visual Servoing Strategies

Multi-focal vision provides two or more vision devices with different fields of view and measurement accuracies. A main advantage of this concept is a flexible allocation of these sensor resources accounting for the current situational and task performance requirements. Particularly, vision devices with large fields of view and low accuracies can be use