A Daisy-Chaining Visual Servoing Approach with Applications in Tracking, Localization, and Mapping

Non

Adaptive Hybrid Visual Servo Regulation of Mobile Robots Based on Fast Homography Decomposition

For the monocular camera-based mobile robot system, an adaptive hybrid visual servo regulation algorithm which is based on a fast homography decomposition method is proposed to drive the mobile robot to its desired position and orientation, even when object’s imaging depth and camera’s position extrinsic parameters are unknown. Firstly, the homography’s particular properties caused by mobile robot’s 2-DOF motion are taken into account to induce a fast homography decomposition method. Secondly, the homography matrix and the extracted orientation error, incorporated with the desired view’s single feature point, are utilized to form an error vector and its open-loop error function. Finally, Lyapunov-based techniques are exploited to construct an adaptive regulation control law, followed by the experimental verification. The experimental results show that the proposed fast homography decomposition method is not only simple and efficient, but also highly precise. Meanwhile, the designed control law can well enable mobile robot position and orientation regulation despite the lack of depth information and camera’s position extrinsic parameters

Monocular Robust Depth Estimation Vision System for Robotic Tasks Interventions in Metallic Targets

Robotic interventions in hazardous scenarios need to pay special attention to safety, as in most cases it is necessary to have an expert operator in the loop. Moreover, the use of a multi-modal Human-Robot Interface allows the user to interact with the robot using manual control in critical steps, as well as semi-autonomous behaviours in more secure scenarios, by using, for example, object tracking and recognition techniques. This paper describes a novel vision system to track and estimate the depth of metallic targets for robotic interventions. The system has been designed for on-hand monocular cameras, focusing on solving lack of visibility and partial occlusions. This solution has been validated during real interventions at the Centre for Nuclear Research (CERN) accelerator facilities, achieving 95% success in autonomous mode and 100% in a supervised manner. The system increases the safety and efficiency of the robotic operations, reducing the cognitive fatigue of the operator during non-critical mission phases. The integration of such an assistance system is especially important when facing complex (or repetitive) tasks, in order to reduce the work load and accumulated stress of the operator, enhancing the performance and safety of the mission

Development of Intelligent Unmanned Aerial Vehicles with Effective Sense and Avoid Capabilities

Ph.DDOCTOR OF PHILOSOPH

Real-Time Visual Servo Control of Two-Link and Three DOF Robot Manipulator

This project presents experimental results of position-based visual servoing control process of a 3R robot using 2 fixed cameras. Visual servoing concerns several field of research including vision systems, robotics and automatic control. This method deal with real time changes in the relative position of the target-object with respect to robot. It is have good accuracy with independency of Manipulator servo control structure from the target pose coordinates are the additional advantages of this method. The applications of visually guided systems are many: from intelligent homes to automotive industry. Visual servoing are also useful for a wide range of applications and it can be used to control many different systems (manipulator arms, mobile robots, aircraft, etc.). Visual servoing systems are generally divide depends on the number of camera, on the position of the camera with respect to the robot, on the design of the error function to robot. This project presents an approach for visual robot control. Existing approaches are increased in such a way that depth and position information of block or object is estimate during the motion of the robot. That is done by the visual tracking of an object throughout the trajectory. Vision designed robotics has been a major research area for more time. However, one of the open and commonly problems in the area is the requirement for exchange of the experiences and ideas. We also include a number of real–time examples from our own research. Forward and inverse kinematics of 3 DOF robot have been done then experiments on image processing, object shape recognition and pose estimation as well as target-block or object in Cartesian system and visual control of robot manipulator have been prescribed. Experimental results obtained from real-time system implementation of visual servo control and tests of 3DOF robot in lab

Towards an autonomous vision-based unmanned aerial system againstwildlife poachers

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.Peer Reviewe

Towards an autonomous vision-based unmanned aerial system against wildlife poachers.

Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $ 213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing