Locally weighted learning model predictivek control for elastic joint robots

This paper proposes an efficient and online learning control system that uses the successful Model Predictive Control (MPC) method in a model based locally weighted learning framework. The new approach named Locally Weighted Learning Model Predictive Control (LWL-MPC) has been proposed as a solution to learn to control complex and nonlinear Elastic Joint Robots (EJR). Elastic Joint Robots are generally difficult to learn to control due to their elastic properties preventing standard model learning techniques from being used, such as learning computed torque control. This paper demonstrates the capability of LWL-MPC to perform online and incremental learning while controlling the joint positions of a real three Degree of Freedom (DoF) EJR. An experiment on a real EJR is presented and LWL-MPC is shown to successfully learn to control the system to follow two different figure of eight trajectories.

The value of books : the fantastic flying books of Mr. Morris Lessmore and the social hieroglyphic of reading

The late eighteenth century witnessed the emergence of new technologies of subjectivity and of the literary. Most obviously, “the novel as a literary form appeared to embody and turn into an object the experience of life itself” (Park), and the novel genre came to both reflect and shape notions of interiority and subjectivity. In this same period, “A shift was taking place in the way people felt and thought about children and the accoutrements of childhood, including books and toys, were implicated in this change” (Lewis). In seeking to understand the relationships between media (e.g. books and toys), genres (e.g. novels and picture books), and modes of subjectivity, Marx’s influential theory of commodity fetishism, whereby “a definite social relation between men, that assumes, in their eyes, the fantastic form of a relation between things”, has served as a productive tool of analysis. The extent to which Marx’s account of commodity fetishism continues to be of use becomes clear when the corollaries between the late eighteenth-century emergence of novels and pictures books as technologies of subjectivity and the early twenty-first century emergence of e-readers and digital texts as technologies of subjectivity are considered. This paper considers the literary technology of Apple’s iPad (first launched in 2010) as a commodity fetish, and the circulation of “apps” as texts made available by and offered as justifications for, this fetish object. The iPad is both book and toy, but is never “only” either; it is arguably a new technology of subjectivity which incorporates but also destabilises categories of reading and playing such as those made familiar by earlier technologies of literature and the self. The particular focus of this paper is on the multimodal versions (app, film, and picture book) of The Fantastic Flying Books of Mr. Morris Lessmore, which are understood here as a narrativisation of commodity fetishism, subjectivity, and the act of reading itself.

Are boards flying blind when it comes to enterprise technology governance?

Considering the sheer speed, complexity and ever changing risk in today’s technology saturated business environment, it’s hardly surprising that the call for digitally savvy directors is increasing. Emerging research suggests serious consequences for boards that continue to ignore or delegate enterprise-level technology governance.

Robust scale initialization for long-range stereo visual odometry

Achieving a robust, accurately scaled pose estimate in long-range stereo presents significant challenges. For large scene depths, triangulation from a single stereo pair is inadequate and noisy. Additionally, vibration and flexible rigs in airborne applications mean accurate calibrations are often compromised. This paper presents a technique for accurately initializing a long-range stereo VO algorithm at large scene depth, with accurate scale, without explicitly computing structure from rigidly fixed camera pairs. By performing a monocular pose estimate over a window of frames from a single camera, followed by adding the secondary camera frames in a modified bundle adjustment, an accurate, metrically scaled pose estimate can be found. To achieve this the scale of the stereo pair is included in the optimization as an additional parameter. Results are presented both on simulated and field gathered data from a fixed-wing UAV flying at significant altitude, where the epipolar geometry is inaccurate due to structural deformation and triangulation from a single pair is insufficient. Comparisons are made with more conventional VO techniques where the scale is not explicitly optimized, and demonstrated over repeated trials to indicate robustness.

Robots for environmental monitoring : significant advancements and applications

Robotic systems are increasingly being utilised as fundamental data-gathering tools by scientists, allowing new perspectives and a greater understanding of the planet and its environmental processes. Today's robots are already exploring our deep oceans, tracking harmful algal blooms and pollution spread, monitoring climate variables, and even studying remote volcanoes. This article collates and discusses the significant advancements and applications of marine, terrestrial, and airborne robotic systems developed for environmental monitoring during the last two decades. Emerging research trends for achieving large-scale environmental monitoring are also reviewed, including cooperative robotic teams, robot and wireless sensor network (WSN) interaction, adaptive sampling and model-aided path planning. These trends offer efficient and precise measurement of environmental processes at unprecedented scales that will push the frontiers of robotic and natural sciences.

Experiments with cooperative control of underwater robots

In this paper we describe cooperative control algorithms for robots and sensor nodes in an underwater environment. Cooperative navigation is defined as the ability of a coupled system of autonomous robots to pool their resources to achieve long-distance navigation and a larger controllability space. Other types of useful cooperation in underwater environments include: exchange of information such as data download and retasking; cooperative localization and tracking; and physical connection (docking) for tasks such as deployment of underwater sensor networks, collection of nodes and rescue of damaged robots. We present experimental results obtained with an underwater system that consists of two very different robots and a number of sensor network modules. We present the hardware and software architecture of this underwater system. We then describe various interactions between the robots and sensor nodes and between the two robots, including cooperative navigation. Finally, we describe our experiments with this underwater system and present data.

Brain-inspired sensor fusion for navigating robots

Current state of the art robot mapping and navigation systems produce impressive performance under a narrow range of robot platform, sensor and environmental conditions, in contrast to animals such as rats that produce “good enough” maps that enable them to function under an incredible range of situations. In this paper we present a rat-inspired featureless sensor-fusion system that assesses the usefulness of multiple sensor modalities based on their utility and coherence for place recognition, without knowledge as to the type of sensor. We demonstrate the system on a Pioneer robot in indoor and outdoor environments with abrupt lighting changes. Through dynamic weighting of the sensors, the system is able to perform correct place recognition and mapping where the static sensor weighting approach fails.

Developing grounded representations for robots through the principles of sensorimotor coordination

Robots currently recognise and use objects through algorithms that are hand-coded or specifically trained. Such robots can operate in known, structured environments but cannot learn to recognise or use novel objects as they appear. This thesis demonstrates that a robot can develop meaningful object representations by learning the fundamental relationship between action and change in sensory state; the robot learns sensorimotor coordination. Methods based on Markov Decision Processes are experimentally validated on a mobile robot capable of gripping objects, and it is found that object recognition and manipulation can be learnt as an emergent property of sensorimotor coordination.

Flying supercapacitors as power smoothing elements in wind generation

This paper presents a capacitor-clamped three-level inverter-based supercapacitor direct integration scheme for wind energy conversion systems. The idea is to increase the capacitance of clamping capacitors with the use of supercapacitors and allow their voltage to vary within a defined range. Even though this unique approach eliminates the need of interfacing dc-dc converters for supercapacitors, the variable voltage operation brings about several challenges. The uneven distribution of space vectors is the major modulation challenge. A space vector modulation method is proposed in this paper to address this issue and to generate undistorted currents even in the presence of dynamic changes in supercapacitor voltages. A supercapacitor voltage equalization algorithm is also presented. Moreover, control strategies of the proposed system are discussed in detail. Simulation and experimental results are presented to verify the efficacy of the proposed system in suppressing short-term wind power fluctuations.

A sparse hybrid map for vision-guided mobile robots

This paper introduces a minimalistic approach to produce a visual hybrid map of a mobile robot’s working environment. The proposed system uses omnidirectional images along with odometry information to build an initial dense posegraph map. Then a two level hybrid map is extracted from the dense graph. The hybrid map consists of global and local levels. The global level contains a sparse topological map extracted from the initial graph using a dual clustering approach. The local level contains a spherical view stored at each node of the global level. The spherical views provide both an appearance signature for the nodes, which the robot uses to localize itself in the environment, and heading information when the robot uses the map for visual navigation. In order to show the usefulness of the map, an experiment was conducted where the map was used for multiple visual navigation tasks inside an office workplace.

Close-quarters Quadrotor flying for a pole inspection with position based visual servoing and high-speed vision

This paper presents a 100 Hz monocular position based visual servoing system to control a quadrotor flying in close proximity to vertical structures approximating a narrow, locally linear shape. Assuming the object boundaries are represented by parallel vertical lines in the image, detection and tracking is achieved using Plücker line representation and a line tracker. The visual information is fused with IMU data in an EKF framework to provide fast and accurate state estimation. A nested control design provides position and velocity control with respect to the object. Our approach is aimed at high performance on-board control for applications allowing only small error margins and without a motion capture system, as required for real world infrastructure inspection. Simulated and ground-truthed experimental results are presented.

Long-term exploration and tours for energy constrained robots with online proprioceptive traversability estimation

This paper is concerned with how a localised and energy-constrained robot can maximise its time in the field by taking paths and tours that minimise its energy expenditure. A significant component of a robot's energy is expended on mobility and is a function of terrain traversability. We estimate traversability online from data sensed by the robot as it moves, and use this to generate maps, explore and ultimately converge on minimum energy tours of the environment. We provide results of detailed simulations and parameter studies that show the efficacy of this approach for a robot moving over terrain with unknown traversability as well as a number of a priori unknown hard obstacles.

Global reconfiguration of a team of networked mobile robots among obstacles

This paper presents a full system demonstration of dynamic sensorbased reconfiguration of a networked robot team. Robots sense obstacles in their environment locally and dynamically adapt their global geometric configuration to conform to an abstract goal shape. We present a novel two-layer planning and control algorithm for team reconfiguration that is decentralised and assumes local (neighbour-to-neighbour) communication only. The approach is designed to be resource-efficient and we show experiments using a team of nine mobile robots with modest computation, communication, and sensing. The robots use acoustic beacons for localisation and can sense obstacles in their local neighbourhood using IR sensors. Our results demonstrate globally-specified reconfiguration from local information in a real robot network, and highlight limitations of standard mesh networks in implementing decentralised algorithms.

A three-level flying-capacitor rectifier based supercapacitor direct integration scheme for distributed generation systems

Supercapacitors are increasingly used as short term energy storage elements in distributed generation systems. The traditional approach in integrating them to the main system is the use of interfacing dc-dc converters which introduce additional costs and power losses. This paper therefore, presents a novel direct integration scheme for supercapacitors and thereby eliminates associated costs and power losses of interfacing converters. The idea is simply to replace ordinary capacitors of three-level flying-capacitor rectifiers with supercapacitors and operate them under variable voltage conditions. An analysis on the reduction of power losses by the proposed system is presented. Furthermore, supercapacitor sizing and implementation issues such as effects of the variable voltage operation and resistive behavior of supercapacitors at high frequencies are also discussed. Simulation results are presented to verify the efficacy of the proposed system in suppressing short term power fluctuations in wind generation system.

An adaptive appearance-based map for long-term topological localization of mobile robots

"This work considers a mobile service robot which uses an appearance-based representation of its workplace as a map, where the current view and the map are used to estimate the current position in the environment. Due to the nature of real-world environments such as houses and offices, where the appearance keeps changing, the internal representation may become out of date after some time. To solve this problem the robot needs to be able to adapt its internal representation continually to the changes in the environment. This paper presents a method for creating an adaptive map for long-term appearance-based localization of a mobile robot using long-term and short-term memory concepts, with omni-directional vision as the external sensor."--publisher website