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We consider the problem of learning from demonstrations to manipulate deformable objects. Recent work [1], [2], [3] has shown promising results that enable robotic manipulation of deformable objects through learning from demonstrations. Their approach is able to generalize from a single demonstration to new test situations, and suggests a nearest neighbor approach to select a demonstration to adapt...
Visual tracking of unknown objects is an essential task in robotic perception, of importance to a wide range of applications. In the general scenario, the robot has no full 3D model of the object beforehand, just the partial view of the object visible in the first video frame. A tracker with this information only will inevitably lose track of the object after occlusions or large out-of-plane rotations...
Real-time and reliable localization is a prerequisite for autonomously performing high-level tasks with micro aerial vehicles(MAVs). Nowadays, most existing methods use vision system for 6DoF pose estimation, which can not work in degraded visual environments. This paper presents an onboard 6DoF pose estimation method for an indoor MAV in challenging GPS-denied degraded visual environments by using...
This paper studies cages of convex polygonal objects using three point fingers. The fingers are said to cage the object when it is impossible to move the object arbitrarily far from its initial placement without penetrating the fingers. We consider a three-parameter model of the relative position of the fingers, which gives complete generality for three point fingers in the plane. We consider robustness...
This paper considers the problem of approximating a kernel matrix in an autoregressive Gaussian process regression (AR-GP) in the presence of measurement noises or natural errors for modeling complex motions of pedestrians in a crowded environment. While a number of methods have been proposed to robustly predict future motions of humans, it still remains as a difficult problem in the presence of measurement...
Myoelectric control has seen decades of research as a potential interface between human and machines. High-density surface electromyography (HDsEMG) non-invasively provides a rich set of signals representing underlying muscle contractions and, at a higher level, human motion intent. Many pattern recognition techniques have been proposed to predict motions based on these signals. However, control schemes...
With the growing demand for deployment of robots in real scenarios, robustness in the perception capabilities for navigation lies at the forefront of research interest, as this forms the backbone of robotic autonomy. Existing place recognition approaches traditionally follow the feature-based bag-of-words paradigm in order to cut down on the richness of information in images. As structural information...
Reliable precision grasping is a pre-condition for manipulation tasks e.g. in assembly and packaging tasks. Especially for small and light objects robust grasping is extremely challenging since even slight errors in the object pose or dimensions lead to irreparable failures caused by unintended finger-object contacts. State of the art techniques address the problem of grasping in the presence of uncertainty...
Underwater environment is characterized by harsh conditions and is difficult to monitor. The CADDY project deals with the development of a companion robot devoted to support and to monitor human operations and activities during the dive. In this scenario the communication and correct reception of messages between the diver and the robot are essential for success of the dive goals. However, the underwater...
The WRSC (World Robotic Sailing Championship) / IRSC (International Robotic Sailing Conference) is an international and annual competition and conference that aims at stimulating the development of autonomous marine robotics and its applications. The competition, originally designed for sailboats, is also opened to motorboats as a separate category since 2013. In this paper, we will present the competition...
The adoption of fault detection and isolation (FDI) techniques is fundamental to ensure high levels of safety and productivity, especially in critical and expensive applications like Autonomous Underwater Vehicles (AUV). This paper describes a comparison between different techniques available in the literature, applied to over-actuated AUVs under single fault condition (SFC) and considering only abrupt...
Speech-based human-robot interaction is often plagued with issues such as reverberation and changes in speaker position that impacts overall performance. In this paper, we show a method in compensating the joint effects of reverberation and the change in speaker position. The acoustic perturbation caused by these two takes its toll on the Automatic Speech Recognition (ASR) and then the Spoken Language...
Robust control maintains stability and performance for a fixed amount of model uncertainty but can be conservative since the model is not updated online. Learning-based control, on the other hand, uses data to improve the model over time but is not typically guaranteed to be robust throughout the process. This paper proposes a novel combination of both ideas: a robust Min-Max Learning-Based Nonlinear...
In this paper, we consider the problem of tracking a reference trajectory for a simplified car model based on unicycle kinematics, whose position only is measured, and where the control input and the measurements are corrupted by independent Gaussian noises. To tackle this problem we devise a novel observer-controller: the invariant Linear Quadratic Gaussian controller (ILQG). It is based on the Linear...
This paper presents a method for stabilizing the attitude of a Hybrid Unmanned Aerial Underwater Vehicle. Firstly, we present aerodynamic and hydrodynamic models for the angular motion of our robot, discussing effects like buoyancy force and added inertia. Next, we apply robust control techniques for both environment, aerial and underwater, based on linear uncertain models with only four vertices...
Scaling down the size and mass of micro aerial vehicles (MAVs) increases their agility and their ability to operate in tight formations. In addition, smaller robots are safer and, as we will show in this paper, more robust to collisions. This paper addresses the development of a pico quadrotor measuring 11 cm from tip to tip, with a mass of 25g. To increase the robustness of the robot to collisions,...
We present an algorithm that seeks to find a set of diverse, short paths through a roadmap graph. The usefulness of a such a set is illustrated in robotic motion planning and routing applications wherein a precomputed roadmap of the environment is partially invalidated by some change, for example, relocation of obstacles or reconfiguration of the robot. Our algorithm employs the heuristic that nearby...
This paper reports on a method to perform robust visual relocalization between temporally separated sets of underwater images gathered by a robot. The place recognition and relocalization problem is more challenging in the underwater environment mainly due to three factors: 1) changes in illumination; 2) long-term changes in the visual appearance of features because of phenomena like biofouling on...
Ensuring safety in partially-known environments is a critical problem in robotics since the environment is perceived through sensors and the environment cannot be completely known ahead of time. Prior work has considered the problem of finding positive control invariant sets (PCIS). However, this approach limits the planning horizon of the motion planner since the PCIS must lie completely in the limited...
We focus on the problem of speech recognition in the presence of nonstationary sudden noise, which is very likely to happen in home environments. To handle this problem, a model compensation method based on a factorial hidden Markov model (FHMM) has been recently introduced. In this architecture, speech and noise processes are modeled in parallel by a phoneme FHMM that is built by combining a clean-speech...
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