This article provides a tutorial introduction to visual servo control of robotic manipulators. Since the topic spans many disciplines our goal is limited providing basic conceptual framework. We begin by reviewing prerequisite topics from robotics and computer vision, including brief review coordinate transformations, velocity representation, description geometric aspects image formation process. then present taxonomy systems. The two major classes systems, position-based image-based are...

This article provides a tutorial introduction to modeling, estimation, and control formultirotor aerial vehicles that includes the common four-rotor or quadrotor case.

Visual place recognition is a challenging problem due to the vast range of ways in which appearance real-world places can vary. In recent years, improvements visual sensing capabilities, an ever-increasing focus on long-term mobile robot autonomy, and ability draw state-of-the-art research other disciplines-particularly computer vision animal navigation neuroscience-have all contributed significant advances systems. This paper presents survey landscape. We start by introducing concepts...

The Robotics Toolbox is a software package that allows MATLAB user to readily create and manipulate datatypes fundamental robotics such as homogeneous transformations, quaternions trajectories. Functions provided, for arbitrary serial-link manipulators, include forward inverse kinematics, Jacobians, dynamics. This article introduces the in tutorial form, with examples chosen demonstrate range of capabilities. complete documentation freely available via anonymous ftp.

In this paper we present a novel platform for underwater sensor networks to be used long-term monitoring of coral reefs and fisheries. The network consists static mobile nodes. nodes communicate point-to-point using high-speed optical communication system integrated into the TinyOS stack, they broadcast an acoustic protocol in stack. have variety sensing capabilities, including cameras, water temperature, pressure. can locate hover above data muling, perform maintenance functions such as...

The application of deep learning in robotics leads to very specific problems and research questions that are typically not addressed by the computer vision machine communities. In this paper we discuss a number robotics-specific learning, reasoning, embodiment challenges for learning. We explain need better evaluation metrics, highlight importance unique robotic simulation, explore spectrum between purely data-driven model-driven approaches. hope provides motivating overview important...

This paper presents a real-time, object-independent grasp synthesis method which can be used for closed-loop grasping.Our proposed Generative Grasping Convolutional Neural Network (GG-CNN) predicts the quality and pose of grasps at every pixel.This one-to-one mapping from depth image overcomes limitations current deep-learning grasping techniques by avoiding discrete sampling candidates long computation times.Additionally, our GG-CNN is orders magnitude smaller while detecting stable with...

This paper is concerned with the application of wireless sensor network (WSN) technology to long-duration and large-scale environmental monitoring. The holy grail a system that can be deployed operated by domain specialists not engineers, but this remains some distance into future. We present our views as why field has progressed less quickly than many envisaged it would over decade ago. use real examples taken from own work in illustrate technological difficulties challenges are entailed...

In image-based visual servo control, where control is effected with respect to the image, there no direct over Cartesian velocities of robot end effector. As a result, executes trajectories that are desirable in but which can be indirect and seemingly contorted space. We introduce partitioned approach overcomes this problem. particular, we decouple x-axis rotational translational components from remaining degrees freedom. Then, guarantee all features remain image throughout entire...

A large-scale, outdoor pervasive computing system uses static and animal-borne nodes to measure the state of a complex comprising climate, soil, pasture, animals. Agriculture faces many challenges, such as climate change, water shortages, labor shortages due an aging urbanized population, increased societal concern about issues animal welfare, food safety, environmental impact. Humanity depends on agriculture for survival, so optimal, profitable, sustainable use our land resources is critical.

We present a novel approach to perform object-independent grasp synthesis from depth images via deep neural networks. Our generative grasping convolutional network (GG-CNN) predicts pixel-wise quality that can be deployed in closed-loop scenarios. GG-CNN overcomes shortcomings existing techniques, namely discrete sampling of candidates and long computation times. The is orders magnitude smaller than other state-of-the-art approaches while achieving better performance, particularly clutter....

Remote monitoring of animal behaviour in the environment can assist managing both and its environmental impact. GPS collars which record locations with high temporal frequency allow researchers to monitor interactions environment. These ground-based sensors be combined remotely-sensed satellite images understand animal-landscape interactions. The key combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from...

This paper introduces a machine learning based system for controlling robotic manipulator with visual perception only. The capability to autonomously learn robot controllers solely from raw-pixel images and without any prior knowledge of configuration is shown the first time. We build upon success recent deep reinforcement develop target reaching three-joint using external observation. A Deep Q Network (DQN) was demonstrated perform after training in simulation. Transferring network real...

In this paper we present a tutorial introduction to two important senses for biological and robotic systems — inertial visual perception. We discuss the fundamentals of these sensing modalities from an engineering perspective. Digital camera chips micro-machined accelerometers gyroscopes are now commodities, when combined with today's available computing can provide robust estimates self-motion as well 3D scene structure, without external infrastructure. complementarity sensors, describe...

We describe a sensor network deployment method using autonomous flying robots. Such networks are suitable for tasks such as large-scale environmental monitoring or command and control in emergency situations. detail the algorithms used measuring connectivity provide experimental data we collected from field trials. A particular focus is on determining gaps of deployed generating plan second, repair, pass to complete connectivity. This project result collaboration between three robotics labs...

In this paper we argue that the focus of much visual servoing literature has been on kinematics control and ignored a number fundamental significant dynamic issues. To end concept is introduced, which concerned with effects due to manipulator machine vision sensor limit performance. These must be explicitly addressed in order achieve high-performance control. The uses simulation experiment investigate feedback issues such as choice compensator, use axis position, velocity or torque...

We present a novel vision-based technique for navigating an unmanned aerial vehicle (UAV) through urban canyons. Our relies on both optic flow and stereo vision information. show that the combination of (stereo flow) is more effective at canyons than either alone. Optic from pair sideways looking cameras used to stay centered in canyon initiate turns junctions, while forward facing head avoid obstacles front. The was tested full autonomous tractor CSIRO part USC helicopter. Experimental...