28 accepted papers
This paper presents a novel strategy for offline estimation of the spatial motion of a multi-link mechanism using Inertial Measurement Unit (IMU) sensors. Accelerometers, gyroscopes and magnetometers are strategically mounted and modeled to maximize measurement accuracy through the past work of iner
Global localization and kidnapping are two challenging problems in robot localization. The popular method, Monte Carlo Localization (MCL) addresses the problem by iteratively updating a set of particles with a “sampling-weighting” loop. Sampling is decisive to the performance of MCL [1]. However, tr
This paper presents a technique for state estimation of a multi-link system having no joint encoders, which can only be partially observed by a camera. To fully observe the system without changing the current configuration, a gyroscope and an accelerometer are attached to each link as dead-reckoning…
The main contribution of this paper is a probabilistic estimator that assists a mobile robot to locate a gas source in an indoor environment. The scenario is that a robot equipped with a gas sensor enters a building after the gas is released due to a leak or explosion. The problem is discretized by…
This paper presents a novel localisation framework based on an omnidirectional camera, targeted at outdoor urban environments. Bearing only information to persistent and easily observable high-level semantic landmarks (such as lamp-posts, street-signs and trees) are perceived using a Convolutional N…
The main contribution of this paper is a novel Extended Kalman Filter (EKF) based localisation scheme that fuses two complementary approaches to outdoor vision based localisation. This EKF is aided by a front end consisting of two Convolutional Neural Networks (CNNs) that provide the necessary perce…
In this letter, we present a novel global structure from motion (SfM) pipeline that is particularly effective in dealing with low-parallax scenes and camera motion collinear with the features that represent the environment structure. It is therefore particularly suitable in Urban SLAM, in which freq
We present the ANBOT, an intelligent robotic coworker for physical human-robot collaboration. The ANBOT system assists workers performing industrial abrasive blasting, shielding them from the large forces experienced during this physically demanding task. The co-operative robotic system combines the…
This paper presents a framework for engaging a target while approaching it from a long distance, using observation from sensors on-board a mobile robot. The proposed framework consists of two multi-stage Bayesian approaches to reliably detect and accurately engage with the target under uncertainties…
The main contribution of this paper is an extended Kalman filter (EKF)based algorithm for estimating the 6 DOF pose of a camera using monocular images of an indoor environment. In contrast to popular visual simultaneous localisation and mapping algorithms, the technique proposed relies on a pre-buil…
In minimal invasive surgery, it is important to rebuild and visualize the latest deformed shape of soft-tissue surfaces to mitigate tissue damages. This letter proposes an innovative Simultaneous localization and mapping (SLAM) algorithm for deformable dense reconstruction of surfaces using a sequen
This letter presents a novel approach to correct errors caused by accumulated scale drift in monocular SLAM. It is shown that the metric scale can be estimated using information gathered through monocular SLAM and image blur due to defocus. A nonlinear least squares optimization problem is formulate
Real-time simultaneous localization and dense mapping is very helpful for providing virtual reality and augmented reality for surgeons or even surgical robots. In this letter, we propose MIS-SLAM: A complete real-time large-scale dense deformable SLAM system with stereoscope in minimal invasive surg
The main contribution of this paper is an invariant extended Kalman filter (EKF) for visual inertial navigation systems (VINS). It is demonstrated that the conventional EKF based VINS is not invariant under the stochastic unobservable transformation, associated with a translation and a rotation abou…
In this letter, we investigate the convergence and consistency properties of an invariant-extended Kalman filter (RI-EKF) based simultaneous localization and mapping (SLAM) algorithm. Basic convergence properties of this algorithm are proven. These proofs do not require the restrictive assumption th
This paper presents an algorithm for localizing an unmanned aerial vehicle (UAV) in GPS denied environments. Localization is performed with respect to a pre-built map of the environment represented using the distance function of a binary mosaic, avoiding the need for extraction and explicit matching…
This paper presents a novel approach to metric scale reconstruction of a three-dimensional (3D) scene using a monocular camera. Using a sequence of images from a monocular camera with a fixed focus lens, metric distance to a set of features in the environment is estimated from image blur due to defo…
This paper presents a generalized multi-stage Bayesian approach for an unmanned aerial vehicle to estimate the location of a mobile target. The major hardware components of the proposed approach are a camera with a fisheye lens and another camera with a normal lens and a pan/tilt unit. With wide ang…
The main contribution of this paper is a planar scan matching algorithm that makes use of the incident angle of a scan point as a feature to enhance the robustness to large relative transformations, particularly in orientation. A new definition of the incident angle is introduced and its consistency…
This paper presents a novel appearance and shape feature, RISAS, which is robust to viewpoint, illumination, scale and rotation variations. RISAS consists of a keypoint detector and a feature descriptor both of which utilise texture and geometric information present in the appearance and shape chann…
In this paper, we study extensions to the Gaussian processes (GPs) continuous occupancy mapping problem. There are two classes of occupancy mapping problems that we particularly investigate. The first problem is related to mapping under pose uncertainty and how to propagate pose estimation uncertain
This work exploits modeling spatial correlation in 2.5D data using Gaussian Processes (GPs), and produces constrained sampling realizations on these models to improve certainty in the predictions by means of integrating additional sparse information. Data organized in 2.5D such as elevation and thic…
The main contribution of this paper is a high frequency, low-complexity, on-board visual-inertial odometry system for quadrotor micro air vehicles. The system consists of an extended Kalman filter (EKF) based state estimation algorithm that fuses information from a low cost MEMS inertial measurement
This paper describes a non-field-of-view (NFOV) localization approach for a mobile robot in an unknown environment based on an acoustic signal combined with the geometrical information from an optical sensor. The approach estimates the location of a target through the mobile robot's sensor observati…
Simultaneous localization and mapping (SLAM) in robotics, and a number of related problems that arise in sensor networks are instances of estimation problems over weighted graphs. This paper studies the relation between the graphical representation of such problems and estimationtheoretic concepts s
This paper presents an active object recognition and pose estimation system for household objects in a highly cluttered environment. A sparse feature model, augmented with the characteristics of features when observed from different viewpoints is used for recognition and pose estimation while a dens…
In this paper we point out an overlooked structure of SLAM that distinguishes it from a generic nonlinear least squares problem. The measurement function in most common forms of SLAM is linear with respect to robot and features positions. Therefore, given an estimate for robot orientation, the condi…
The problem of active perception with an autonomous robot is studied in this paper. It is proposed that the exploratory behavior of the robot be controlled using mutual information (MI) surfaces between the current map and a one-step look ahead measurements. MI surfaces highlight informative areas f…