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  • Elastica: A compliant mechanics environment for soft robotic control
    arXiv.cs.RO Pub Date : 2020-09-17
    Noel Naughton; Jiarui Sun; Arman Tekinalp; Girish Chowdhary; Mattia Gazzola

    Soft robots are notoriously hard to control. This is partly due to the scarcity of models able to capture their complex continuum mechanics, resulting in a lack of control methodologies that take full advantage of body compliance. Currently available simulation methods are either too computational demanding or overly simplistic in their physical assumptions, leading to a paucity of available simulation

    更新日期:2020-09-20
  • Can ROS be used securely in industry? Red teaming ROS-Industrial
    arXiv.cs.RO Pub Date : 2020-09-17
    Víctor Mayoral-Vilches; Martin Pinzger; Stefan Rass; Bernhard Dieber; Endika Gil-Uriarte

    With its growing use in industry, ROS is rapidly becoming a standard in robotics. While developments in ROS 2 show promise, the slow adoption cycles in industry will push widespread ROS 2 industrial adoption years from now. ROS will prevail in the meantime which raises the question: can ROS be used securely for industrial use cases even though its origins didn't consider it? The present study analyzes

    更新日期:2020-09-20
  • POMP: Pomcp-based Online Motion Planning for active visual search in indoor environments
    arXiv.cs.RO Pub Date : 2020-09-17
    Yiming Wang; Francesco Giuliari; Riccardo Berra; Alberto Castellini; Alessio Del Bue; Alessandro Farinelli; Marco Cristani; Francesco Setti

    In this paper we focus on the problem of learning an optimal policy for Active Visual Search (AVS) of objects in known indoor environments with an online setup. Our POMP method uses as input the current pose of an agent (e.g. a robot) and a RGB-D frame. The task is to plan the next move that brings the agent closer to the target object. We model this problem as a Partially Observable Markov Decision

    更新日期:2020-09-20
  • Voice Controlled Upper Body Exoskeleton: A Development For Industrial Application
    arXiv.cs.RO Pub Date : 2020-09-17
    Shivam Tripathy; Rohan Panicker; Shubh Shrey; Rutvik Naik; S S Pachpore

    An exoskeleton is a wearable electromechanical structure that is intended to resemble and allow movements in a manner similar to the human skeletal system. They can be used by both disabled and able people alike to increase physical strength in carrying out tasks that would be otherwise difficult, or as a rehabilitation device to aid in physiotherapeutic activities of a weakened body part. This paper

    更新日期:2020-09-20
  • SwarmCCO: Probabilistic Reactive Collision Avoidance for Quadrotor Swarms under Uncertainty
    arXiv.cs.RO Pub Date : 2020-09-16
    Senthil Hariharan Arul; Dinesh Manocha

    We present decentralized collision avoidance algorithms for quadrotor swarms operating under uncertain state estimation. Our approach exploits the differential flatness property and feedforward linearization to approximate the quadrotor dynamics and reciprocal collision avoidance. We account for the uncertainty in position and velocity by formulating the collision constraints as chance constraints

    更新日期:2020-09-20
  • Multimodal Safety-Critical Scenarios Generation for Decision-Making Algorithms Evaluation
    arXiv.cs.RO Pub Date : 2020-09-16
    Wenhao Ding; Baiming Chen; Bo Li; Kim Ji Eun; Ding Zhao

    Existing neural network-based autonomous systems are shown to be vulnerable against adversarial attacks, therefore sophisticated evaluation on their robustness is of great importance. However, evaluating the robustness only under the worst-case scenarios based on known attacks is not comprehensive, not to mention that some of them even rarely occur in the real world. In addition, the distribution of

    更新日期:2020-09-20
  • Learning to Identify Physical Parameters from Video Using Differentiable Physics
    arXiv.cs.RO Pub Date : 2020-09-17
    Rama Krishna Kandukuri; Jan Achterhold; Michael Möller; Jörg Stückler

    Video representation learning has recently attracted attention in computer vision due to its applications for activity and scene forecasting or vision-based planning and control. Video prediction models often learn a latent representation of video which is encoded from input frames and decoded back into images. Even when conditioned on actions, purely deep learning based architectures typically lack

    更新日期:2020-09-20
  • Suction-based Soft Robotic Gripping of Rough and Irregular Parts
    arXiv.cs.RO Pub Date : 2020-09-17
    Sukho Song; Dirk-Michael Drotlef; Donghoon Son; Anastasia Koivikko; Metin Sitti

    Recently, suction-based robotic systems with microscopic features or active suction components have been proposed to grip rough and irregular surfaces. However, sophisticated fabrication methods or complex control systems are required for such systems, and robust attachment to rough real-world surfaces still remains a grand challenge. Here, we propose a fully soft robotic gripper, where a flat elastic

    更新日期:2020-09-20
  • Post Quantum Secure Command and Control of Mobile Agents : Inserting quantum-resistant encryption schemes in the Secure Robot Operating System
    arXiv.cs.RO Pub Date : 2020-09-16
    Richa Varma; Chris Melville; Claudio Pinello; Tuhin Sahai

    The secure command and control (C&C) of mobile agents arises in various settings including unmanned aerial vehicles, single pilot operations in commercial settings, and mobile robots to name a few. As more and more of these applications get integrated into aerospace and defense use cases, the security of the communication channel between the ground station and the mobile agent is of increasing importance

    更新日期:2020-09-20
  • Using Sensory Time-cue to enable Unsupervised Multimodal Meta-learning
    arXiv.cs.RO Pub Date : 2020-09-16
    Qiong Liu; Yanxia Zhang

    As data from IoT (Internet of Things) sensors become ubiquitous, state-of-the-art machine learning algorithms face many challenges on directly using sensor data. To overcome these challenges, methods must be designed to learn directly from sensors without manual annotations. This paper introduces Sensory Time-cue for Unsupervised Meta-learning (STUM). Different from traditional learning approaches

    更新日期:2020-09-20
  • MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control
    arXiv.cs.RO Pub Date : 2020-09-16
    Boris Ivanovic; Amine Elhafsi; Guy Rosman; Adrien Gaidon; Marco Pavone

    Reasoning about human motion is a core component of modern human-robot interactive systems. In particular, one of the main uses of behavior prediction in autonomous systems is to inform ego-robot motion planning and control. However, a majority of planning and control algorithms reason about system dynamics rather than the predicted agent tracklets that are commonly output by trajectory forecasting

    更新日期:2020-09-18
  • PL-VINS: Real-Time Monocular Visual-Inertial SLAM with Point and Line
    arXiv.cs.RO Pub Date : 2020-09-16
    Qiang Fu; Jialong Wang; Hongshan Yu; Islam Ali; Feng Guo; Hong Zhang

    Leveraging line features to improve location accuracy of point-based visual-inertial SLAM (VINS) is gaining importance as they provide additional constraint of scene structure regularity, however, real-time performance has not been focused. This paper presents PL-VINS, a real-time optimization-based monocular VINS method with point and line, developed based on state-of-the-art point-based VINS-Mono

    更新日期:2020-09-18
  • Cell A* for Navigation of Unmanned Aerial Vehicles in Partially-known Environments
    arXiv.cs.RO Pub Date : 2020-09-16
    Wenjian Hao; Rongyao Wang; Alexander Krolicki; Yiqiang Han

    Proper path planning is the first step of robust and efficient autonomous navigation for mobile robots. Meanwhile, it is still challenging for robots to work in a complex environment without complete prior information. This paper presents an extension to the A* search algorithm and its variants to make the path planning stable with less computational burden while handling long-distance tasks. The implemented

    更新日期:2020-09-18
  • Related by Similarity II: Poncelet 3-Periodics in the Homothetic Pair and the Brocard Porism
    arXiv.cs.RO Pub Date : 2020-09-16
    Dan Reznik; Ronaldo Garcia

    Previously we showed the family of 3-periodics in the elliptic billiard (confocal pair) is the image under a variable similarity transform of poristic triangles (those with non-concentric, fixed incircle and circumcircle). Both families conserve the ratio of inradius to circumradius and therefore also the sum of cosines. This is consisten with the fact that a similarity preserves angles. Here we study

    更新日期:2020-09-18
  • Distributed formation maneuver control by manipulating the complex Laplacian
    arXiv.cs.RO Pub Date : 2020-09-16
    Hector Garcia de Marina

    This paper proposes a novel maneuvering technique for the complex-Laplacian-based formation control. We show how to modify the original weights that build the Laplacian such that a designed steady-state motion of the desired shape emerges from the local interactions among the agents. These collective motions can be exploited to solve problems such as the shaped consensus (the rendezvous with a particular

    更新日期:2020-09-18
  • Domain Adaptation for Outdoor Robot Traversability Estimation from RGB data with Safety-Preserving Loss
    arXiv.cs.RO Pub Date : 2020-09-16
    Simone Palazzo; Dario C. Guastella; Luciano Cantelli; Paolo Spadaro; Francesco Rundo; Giovanni Muscato; Daniela Giordano; Concetto Spampinato

    Being able to estimate the traversability of the area surrounding a mobile robot is a fundamental task in the design of a navigation algorithm. However, the task is often complex, since it requires evaluating distances from obstacles, type and slope of terrain, and dealing with non-obvious discontinuities in detected distances due to perspective. In this paper, we present an approach based on deep

    更新日期:2020-09-18
  • BOP Challenge 2020 on 6D Object Localization
    arXiv.cs.RO Pub Date : 2020-09-15
    Tomas Hodan; Martin Sundermeyer; Bertram Drost; Yann Labbe; Eric Brachmann; Frank Michel; Carsten Rother; Jiri Matas

    This paper presents the evaluation methodology, datasets, and results of the BOP Challenge 2020, the third in a series of public competitions organized with the goal to capture the status quo in the field of 6D object pose estimation from an RGB-D image. In 2020, to reduce the domain gap between synthetic training and real test RGB images, the participants were provided 350K photorealistic trainining

    更新日期:2020-09-18
  • Autonomous Navigation in Unknown Environments with Sparse Bayesian Kernel-based Occupancy Mapping
    arXiv.cs.RO Pub Date : 2020-09-15
    Thai Duong; Michael Yip; Nikolay Atanasov

    This paper focuses on online occupancy mapping and real-time collision checking onboard an autonomous robot navigating in a large unknown environment. Commonly used voxel and octree map representations can be easily maintained in a small environment but have increasing memory requirements as the environment grows. We propose a fundamentally different approach for occupancy mapping, in which the boundary

    更新日期:2020-09-16
  • Event-Driven Visual-Tactile Sensing and Learning for Robots
    arXiv.cs.RO Pub Date : 2020-09-15
    Tasbolat Taunyazov; Weicong Sng; Hian Hian See; Brian Lim; Jethro Kuan; Abdul Fatir Ansari; Benjamin C. K. Tee; Harold Soh

    This work contributes an event-driven visual-tactile perception system, comprising a novel biologically-inspired tactile sensor and multi-modal spike-based learning. Our neuromorphic fingertip tactile sensor, NeuTouch, scales well with the number of taxels thanks to its event-based nature. Likewise, our Visual-Tactile Spiking Neural Network (VT-SNN) enables fast perception when coupled with event sensors

    更新日期:2020-09-16
  • RaLL: End-to-end Radar Localization on Lidar Map Using Differentiable Measurement Model
    arXiv.cs.RO Pub Date : 2020-09-15
    Huan Yin; Yue Wang; Runjian Chen; Rong Xiong

    Radar sensor provides lighting and weather invariant sensing, which is naturally suitable for long-term localization in outdoor scenes. On the other hand, the most popular available map currently is built by lidar. In this paper, we propose a deep neural network for end-to-end learning of radar localization on lidar map to bridge the gap. We first embed both sensor modals into a common feature space

    更新日期:2020-09-16
  • Approximate Piecewise Constant Curvature Equivalent Model and Their Application to Continuum Robot Configuration Estimation
    arXiv.cs.RO Pub Date : 2020-09-15
    Hao Cheng; Houde Liu; Xueqian Wang; Bin Liang

    The continuum robot has attracted more attention for its flexibility. Continuum robot kinematics models are the basis for further perception, planning, and control. The design and research of continuum robots are usually based on the assumption of piecewise constant curvature (PCC). However, due to the influence of friction, etc., the actual motion of the continuum robot is approximate piecewise constant

    更新日期:2020-09-16
  • 3D_DEN: Open-ended 3D Object Recognition using Dynamically Expandable Networks
    arXiv.cs.RO Pub Date : 2020-09-15
    Sudhakaran Jain; Hamidreza Kasaei

    Service robots, in general, have to work independently and adapt to the dynamic changes in the environment. One important aspect in such scenarios is to continually learn to recognize new objects when they become available. This combines two main research problems namely continual learning and 3D object recognition. Most of the existing research approaches include the use of deep Convolutional Neural

    更新日期:2020-09-16
  • Socially competent robots: adaptation improves leadership performance in groups of live fish
    arXiv.cs.RO Pub Date : 2020-09-14
    Tim Landgraf; Hauke J. Moenck; Gregor H. W. Gebhardt; Nils Weimar; Mathis Hocke; Moritz Maxeiner; Lea Musiolek; Jens Krause; David Bierbach

    Collective motion is commonly modeled with simple interaction rules between agents. Yet in nature, numerous observables vary within and between individuals and it remains largely unknown how animals respond to this variability, and how much of it may be the result of social responses. Here, we hypothesize that Guppies (\textit{Poecilia reticulata}) respond to avoidance behaviors of their shoal mates

    更新日期:2020-09-16
  • CoVR: A Large-Scale Force-Feedback Robotic Interface for Non-Deterministic Scenarios in VR
    arXiv.cs.RO Pub Date : 2020-09-15
    Elodie Bouzbib; Gilles Bailly; Sinan Haliyo; Pascal Frey

    We present CoVR, a novel robotic interface providing strong kinesthetic feedback (100 N) in a room-scale VR arena. It consists of a physical column mounted on a 2D Cartesian ceiling robot (XY displacements) with the capacity of (1) resisting to body-scaled users' actions such as pushing or leaning; (2) acting on the users by pulling or transporting them as well as (3) carrying multiple potentially

    更新日期:2020-09-16
  • Attention-SLAM: A Visual Monocular SLAM Learning from Human Gaze
    arXiv.cs.RO Pub Date : 2020-09-15
    Jinquan Li; Ling Pei; Danping Zou; Songpengcheng Xia; Qi Wu; Tao Li; Zhen Sun; Wenxian Yu

    This paper proposes a novel simultaneous localization and mapping (SLAM) approach, namely Attention-SLAM, which simulates human navigation mode by combining a visual saliency model (SalNavNet) with traditional monocular visual SLAM. Most SLAM methods treat all the features extracted from the images as equal importance during the optimization process. However, the salient feature points in scenes have

    更新日期:2020-09-16
  • Miniaturized Circuitry for Capacitive Self-sensing and Closed-loop Control of Soft Electrostatic Transducers
    arXiv.cs.RO Pub Date : 2020-09-15
    Khoi Ly; Nicholas Kellaris; Dade McMorris; Brian K. Johnson; Eric Acome; Vani Sundaram; Mantas Naris; J. Sean Humbert; Mark E. Rentschler; Christoph Keplinger; Nikolaus Correll

    Soft robotics is a field of robotic system design characterized by materials and structures that exhibit large-scale deformation, high compliance, and rich multifunctionality. The incorporation of soft and deformable structures endows soft robotic systems with the compliance and resiliency that makes them well-adapted for unstructured and dynamic environments. While actuation mechanisms for soft robots

    更新日期:2020-09-16
  • Design and Workspace Characterisation of Malleable Robots
    arXiv.cs.RO Pub Date : 2020-09-14
    Angus B. Clark; Nicolas Rojas

    For the majority of tasks performed by traditional serial robot arms, such as bin picking or pick and place, only two or three degrees of freedom (DOF) are required for motion; however, by augmenting the number of degrees of freedom, further dexterity of robot arms for multiple tasks can be achieved. Instead of increasing the number of joints of a robot to improve flexibility and adaptation, which

    更新日期:2020-09-15
  • A Task Allocation Approach for Human-Robot Collaboration in Product Defects Inspection Scenarios
    arXiv.cs.RO Pub Date : 2020-09-14
    Hossein Karami; Kourosh Darvish; Fulvio Mastrogiovanni

    The presence and coexistence of human operators and collaborative robots in shop-floor environments raises the need for assigning tasks to either operators or robots, or both. Depending on task characteristics, operator capabilities and the involved robot functionalities, it is of the utmost importance to design strategies allowing for the concurrent and/or sequential allocation of tasks related to

    更新日期:2020-09-15
  • A Multisensory Learning Architecture for Rotation-invariant Object Recognition
    arXiv.cs.RO Pub Date : 2020-09-14
    Murat Kirtay; Guido Schillaci; Verena V. Hafner

    This study presents a multisensory machine learning architecture for object recognition by employing a novel dataset that was constructed with the iCub robot, which is equipped with three cameras and a depth sensor. The proposed architecture combines convolutional neural networks to form representations (i.e., features) for grayscaled color images and a multi-layer perceptron algorithm to process depth

    更新日期:2020-09-15
  • A Survey of FPGA-Based Robotic Computing
    arXiv.cs.RO Pub Date : 2020-09-13
    Zishen Wan; Bo Yu; Thomas Yuang Li; Jie Tang; Yuhao Zhu; Yu Wang; Arijit Raychowdhury; Shaoshan Liu

    Recent researches on robotics have shown significant improvement, spanning from algorithms, mechanics to hardware architectures. Robotics, including manipulators, legged robots, drones, and autonomous vehicles, are now widely applied in diverse scenarios. However, the high computation and data complexity of robotic algorithms pose great challenges to its applications. On the one hand, CPU platform

    更新日期:2020-09-15
  • MPC-Based Hierarchical Task Space Control of Underactuated and Constrained Robots for Execution of Multiple Tasks
    arXiv.cs.RO Pub Date : 2020-09-13
    Jaemin Lee; Seung Hyeon Bang; Efstathios Bakolas; Luis Sentis

    This paper proposes an MPC-based controller to efficiently execute multiple hierarchical tasks for underactuated and constrained robotic systems. Existing task-space controllers or whole-body controllers solve instantaneous optimization problems given task trajectories and the robot plant dynamics. However, the task-space control method we propose here relies on the prediction of future state trajectories

    更新日期:2020-09-15
  • Towards Automatic Manipulation of Intra-cardiac Echocardiography Catheter
    arXiv.cs.RO Pub Date : 2020-09-12
    Young-Ho Kim; Jarrod Collins; Zhongyu Li; Ponraj Chinnadurai; Ankur Kapoor; C. Huie Lin; Tommaso Mansi

    Intra-cardiac Echocardiography (ICE) has been evolving as a real-time imaging modality of choice for guiding electrophiosology and structural heart interventions. ICE provides real-time imaging of anatomy, catheters, and complications such as pericardial effusion or thrombus formation. However, there now exists a high cognitive demand on physicians with the increased reliance on intraprocedural imaging

    更新日期:2020-09-15
  • SeaShark: Towards a Modular Multi-Purpose Man-Portable AUV
    arXiv.cs.RO Pub Date : 2020-09-12
    Jesper Haahr Christensen; Marco Jacobi; Martin Clemmensen Rotne; Morten Soede Nielsen; Max Abildgaard; Claus Eriksen; Lars Valdemar Mogensen

    In this work, we present the SeaShark AUV: a modular, easily configurable, one-man portable micro-AUV. The SeaShark AUV is conceived as modular parts that fit around a central main tube, which holds battery and other vital parts. The head unit comprises easy exhangeable, stackable, and 360 degree rotatable payload sections to quickly obtain a suitable configuration for many objectives. We employ navigation

    更新日期:2020-09-15
  • Automatic Trajectory Synthesis for Real-Time Temporal Logic
    arXiv.cs.RO Pub Date : 2020-09-14
    Rafael Rodrigues da Silva; Vince Kurtz; Hai Lin

    Many safety-critical systems must achieve high-level task specifications with guaranteed safety and correctness. Much recent progress towards this goal has been made through controller synthesis from temporal logic specifications. Existing approaches, however, have been limited to relatively short and simple specifications. Furthermore, existing methods either consider some prior discretization of

    更新日期:2020-09-15
  • Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction
    arXiv.cs.RO Pub Date : 2020-09-12
    Haruki Nishimura; Boris Ivanovic; Adrien Gaidon; Marco Pavone; Mac Schwager

    This paper presents a novel online framework for safe crowd-robot interaction based on risk-sensitive stochastic optimal control, wherein the risk is modeled by the entropic risk measure. The sampling-based model predictive control relies on mode insertion gradient optimization for this risk measure as well as Trajectron++, a state-of-the-art generative model that produces multimodal probabilistic

    更新日期:2020-09-15
  • Autonomous Hybrid Ground/Aerial Mobility in Unknown Environments
    arXiv.cs.RO Pub Date : 2020-09-11
    David D. Fan; Rohan Thakker; Tara Bartlett; Meriem Ben Miled; Leon Kim; Evangelos Theodorou; Ali-akbar Agha-mohammadi

    Hybrid ground and aerial vehicles can possess distinct advantages over ground-only or flight-only designs in terms of energy savings and increased mobility. In this work we outline our unified framework for controls, planning, and autonomy of hybrid ground/air vehicles. Our contribution is three-fold: 1) We develop a control scheme for the control of passive two-wheeled hybrid ground/aerial vehicles

    更新日期:2020-09-15
  • Rumor-robust Decentralized Gaussian Process Learning, Fusion, and Planning for Modeling Multiple Moving Targets
    arXiv.cs.RO Pub Date : 2020-09-13
    Chang Liu; Zhihao Liao; Silvia Ferrari

    This paper presents a decentralized Gaussian Process (GP) learning, fusion, and planning (RESIN) formalism for mobile sensor networks to actively learn target motion models. RESIN is characterized by both computational and communication efficiency, and the robustness to rumor propagation in sensor networks. By using the weighted exponential product rule and the Chernoff information, a rumor-robust

    更新日期:2020-09-15
  • Multi-Spectral Image Synthesis for Crop/Weed Segmentation in Precision Farming
    arXiv.cs.RO Pub Date : 2020-09-12
    Mulham Fawakherji; Ciro Potena; Alberto Pretto; Domenico D. Bloisi; Daniele Nardi

    An effective perception system is a fundamental component for farming robots, as it enables them to properly perceive the surrounding environment and to carry out targeted operations. The most recent approaches make use of state-of-the-art machine learning techniques to learn an effective model for the target task. However, those methods need a large amount of labelled data for training. A recent approach

    更新日期:2020-09-15
  • Programming Active Granular Matter with Mechanically Induced Phase Changes
    arXiv.cs.RO Pub Date : 2020-09-12
    Shengkai Li; Bahnisikha Dutta; Sarah Cannon; Joshua J. Daymude; Ram Avinery; Enes Aydin; Andréa W. Richa; Daniel I. Goldman; Dana Randall

    Emergent behavior of particles on a lattice has been analyzed extensively in mathematics with possible analogies to physical phenomena such as clustering in colloidal systems. While there exists a rich pool of interesting results, most are yet to be explored physically due to the lack of experimental validation. Here we show how the individual moves of robotic agents are tightly mapped to a discrete

    更新日期:2020-09-15
  • Embodied Visual Navigation with Automatic Curriculum Learning in Real Environments
    arXiv.cs.RO Pub Date : 2020-09-11
    Steven D. Morad; Roberto Mecca; Rudra P. K. Poudel; Stephan Liwicki; Roberto Cipolla

    We present NavACL, a method of automatic curriculum learning tailored to the navigation task. NavACL is simple to train and efficiently selects relevant tasks using geometric features. In our experiments, deep reinforcement learning agents trained using NavACL in collision-free environments significantly outperform state-of-the-art agents trained with uniform sampling -- the current standard. Furthermore

    更新日期:2020-09-14
  • A Toolkit to Generate Social Navigation Datasets
    arXiv.cs.RO Pub Date : 2020-09-11
    Rishabh Baghel; Aditya Kapoor; Pilar Bachiller; Ronit R. Jorvekar; Daniel Rodriguez-Criado; Luis J. Manso

    Social navigation datasets are necessary to assess social navigation algorithms and train machine learning algorithms. Most of the currently available datasets target pedestrians' movements as a pattern to be replicated by robots. It can be argued that one of the main reasons for this to happen is that compiling datasets where real robots are manually controlled, as they would be expected to behave

    更新日期:2020-09-14
  • The Robotic Vision Scene Understanding Challenge
    arXiv.cs.RO Pub Date : 2020-09-11
    David Hall; Ben Talbot; Suman Raj Bista; Haoyang Zhang; Rohan Smith; Feras Dayoub; Niko Sünderhauf

    Being able to explore an environment and understand the location and type of all objects therein is important for indoor robotic platforms that must interact closely with humans. However, it is difficult to evaluate progress in this area due to a lack of standardized testing which is limited due to the need for active robot agency and perfect object ground-truth. To help provide a standard for testing

    更新日期:2020-09-14
  • Towards Safe Locomotion Navigation in Partially Observable Environments with Uneven Terrain
    arXiv.cs.RO Pub Date : 2020-09-10
    Jonas Warnke; Abdulaziz Shamsah; Yingke Li; Ye Zhao

    This study proposes an integrated task and motion planning method for dynamic locomotion in partially observable environments with multi-level safety guarantees. This layered planning framework is composed of a high-level symbolic task planner and a low-level phase-space motion planner. A belief abstraction at the task planning level enables belief estimation of dynamic obstacle locations and guarantees

    更新日期:2020-09-14
  • Sentinel: An Onboard System for Intelligent Vehicles to Reduce Traffic Delay during Freeway Incidents
    arXiv.cs.RO Pub Date : 2020-09-10
    Goodarz Mehr; Azim Eskandarian

    This paper introduces Sentinel, an onboard system that guides the lane change behavior of intelligent vehicles during a freeway incident to reduce congestion and delay. Sentinel is built upon a probabilistic prediction model that uses several traffic- and driver-related parameters to estimate the probability of reaching a target position on the road using a number of lane changes. When an incident

    更新日期:2020-09-14
  • Keypoints into the Future: Self-Supervised Correspondence in Model-Based Reinforcement Learning
    arXiv.cs.RO Pub Date : 2020-09-10
    Lucas Manuelli; Yunzhu Li; Pete Florence; Russ Tedrake

    Predictive models have been at the core of many robotic systems, from quadrotors to walking robots. However, it has been challenging to develop and apply such models to practical robotic manipulation due to high-dimensional sensory observations such as images. Previous approaches to learning models in the context of robotic manipulation have either learned whole image dynamics or used autoencoders

    更新日期:2020-09-14
  • Solving Challenging Dexterous Manipulation Tasks With Trajectory Optimisation and Reinforcement Learning
    arXiv.cs.RO Pub Date : 2020-09-09
    Henry Charlesworth; Giovanni Montana

    Training agents to autonomously learn how to use anthropomorphic robotic hands has the potential to lead to systems capable of performing a multitude of complex manipulation tasks in unstructured and uncertain environments. In this work, we first introduce a suite of challenging simulated manipulation tasks that current reinforcement learning and trajectory optimisation techniques find difficult. These

    更新日期:2020-09-14
  • A First Step Towards Distribution Invariant Regression Metrics
    arXiv.cs.RO Pub Date : 2020-09-10
    Mario Michael Krell; Bilal Wehbe

    Regression evaluation has been performed for decades. Some metrics have been identified to be robust against shifting and scaling of the data but considering the different distributions of data is much more difficult to address (imbalance problem) even though it largely impacts the comparability between evaluations on different datasets. In classification, it has been stated repeatedly that performance

    更新日期:2020-09-14
  • Practical Cross-modal Manifold Alignment for Grounded Language
    arXiv.cs.RO Pub Date : 2020-09-01
    Andre T. Nguyen; Luke E. Richards; Gaoussou Youssouf Kebe; Edward Raff; Kasra Darvish; Frank Ferraro; Cynthia Matuszek

    We propose a cross-modality manifold alignment procedure that leverages triplet loss to jointly learn consistent, multi-modal embeddings of language-based concepts of real-world items. Our approach learns these embeddings by sampling triples of anchor, positive, and negative data points from RGB-depth images and their natural language descriptions. We show that our approach can benefit from, but does

    更新日期:2020-09-14
  • What am I allowed to do here?: Online Learning of Context-Specific Norms by Pepper
    arXiv.cs.RO Pub Date : 2020-08-22
    Ali Ayub; Alan R. Wagner

    Social norms support coordination and cooperation in society. With social robots becoming increasingly involved in our society, they also need to follow the social norms of the society. This paper presents a computational framework for learning contexts and the social norms present in a context in an online manner on a robot. The paper utilizes a recent state-of-the-art approach for incremental learning

    更新日期:2020-09-14
  • Distributed Variable-Baseline Stereo SLAM from two UAVs
    arXiv.cs.RO Pub Date : 2020-09-10
    Marco Karrer; Margarita Chli

    VIO has been widely used and researched to control and aid the automation of navigation of robots especially in the absence of absolute position measurements, such as GPS. However, when observable landmarks in the scene lie far away from the robot's sensor suite, as it is the case at high altitude flights, the fidelity of estimates and the observability of the metric scale degrades greatly for these

    更新日期:2020-09-11
  • Defining Adaptive Proxemic Zones for Activity-aware Navigation
    arXiv.cs.RO Pub Date : 2020-09-10
    Jonatan Gines Clavero; Francisco Martin Rico; Francisco J. Rodriguez-Lera; Jose Miguel Guerrero Hernandez; Vicente Matellan Olivera

    Many of the tasks that a service robot can perform at home involve navigation skills. In a real world scenario, the navigation system should consider individuals beyond just objects, theses days it is necessary to offer particular and dynamic representation in the scenario in order to enhance the HRI experience. In this paper, we use the proxemic theory to do this representation. The proxemic zones

    更新日期:2020-09-11
  • Path planning model of mobile robots in the context of crowds
    arXiv.cs.RO Pub Date : 2020-09-10
    W. Z. Wang; R. Q. Wang; G. H. Chen

    Robot path planning model based on RNN and visual quality evaluation in the context of crowds is analyzed in this paper. Mobile robot path planning is the key to robot navigation and an important field in robot research. Let the motion space of the robot be a two-dimensional plane, and the motion of the robot is regarded as a kind of motion under the virtual artificial potential field force when the

    更新日期:2020-09-11
  • Proactive Estimation of Occlusions and Scene Coverage for Planning Next Best Views in an Unstructured Representation
    arXiv.cs.RO Pub Date : 2020-09-09
    Rowan Border; Jonathan D. Gammell

    The process of planning views to observe a scene is known as the Next Best View (NBV) problem. Approaches often aim to obtain high-quality scene observations while reducing the number of views, travel distance and computational cost. Considering occlusions and scene coverage can significantly reduce the number of views and travel distance required to obtain an observation. Structured representations

    更新日期:2020-09-11
  • Analysis of Theoretical and Numerical Properties of Sequential Convex Programming for Continuous-Time Optimal Control
    arXiv.cs.RO Pub Date : 2020-09-10
    Riccardo Bonalli; Thomas Lew; Marco Pavone

    Through the years, Sequential Convex Programming (SCP) has gained great interest as an efficient tool for non-convex optimal control. Despite the large number of existing algorithmic frameworks, only a few are accompanied by rigorous convergence analysis, which are often only tailored to discrete-time problem formulations. In this paper, we present a unifying theoretical analysis of a fairly general

    更新日期:2020-09-11
  • Unmanned air-traffic management (UTM): Formalization, a prototype implementation, and performance evaluation
    arXiv.cs.RO Pub Date : 2020-09-10
    Chiao HsiehUniversity of Illinois at Urbana-Champaign; Hussein SibaiUniversity of Illinois at Urbana-Champaign; Hebron TaylorUniversity of Illinois at Urbana-Champaign; Sayan MitraUniversity of Illinois at Urbana-Champaign

    Unmanned Aircraft Systems (UAS) are being increasingly used in delivery, infrastructure surveillance, fire-fighting, and agriculture. According to the Federal Aviation Administration (FAA), the number of active small commercial unmanned aircraft is going to grow from 385K in 2019 to 828K by 2024. UAS traffic management (UTM) system for low-altitude airspace is therefore immediately necessary for its

    更新日期:2020-09-11
  • All-Weather sub-50-cm Radar-Inertial Positioning
    arXiv.cs.RO Pub Date : 2020-09-09
    Lakshay Narula; Peter A. Iannucci; Todd E. Humphreys

    Deployment of automated ground vehicles beyond the confines of sunny and dry climes will require sub-lane-level positioning techniques based on radio waves rather than near-visible-light radiation. Like human sight, lidar and cameras perform poorly in low-visibility conditions. This paper develops and demonstrates a novel technique for robust sub-50-cm-accurate urban ground vehicle positioning based

    更新日期:2020-09-11
  • A Minimum Energy Filter for Localisation of an Unmanned Aerial Vehicle
    arXiv.cs.RO Pub Date : 2020-09-10
    Jack Henderson; Mohammad Zamani; Robert Mahony; Jochen Trumpf

    Accurate localisation of unmanned aerial vehicles is vital for the next generation of automation tasks. This paper proposes a minimum energy filter for velocity-aided pose estimation on the extended special Euclidean group. The approach taken exploits the Lie-group symmetry of the problem to combine Inertial Measurement Unit (IMU) sensor output with landmark measurements into a robust and high performance

    更新日期:2020-09-11
  • Resilient Task Allocation in Heterogeneous Multi-Robot Systems
    arXiv.cs.RO Pub Date : 2020-09-09
    Siddharth Mayya; David Saldaña; Vijay Kumar

    For a multi-robot system equipped with heterogeneous capabilities, this paper presents a mechanism to allocate robots to tasks in a resilient manner when anomalous environmental conditions such as weather events or adversarial attacks affect the performance of robots within the tasks. Our primary objective is to ensure that each task is assigned the requisite level of resources, measured as the aggregated

    更新日期:2020-09-11
  • Integrated Benchmarking and Design for Reproducible and Accessible Evaluation of Robotic Agents
    arXiv.cs.RO Pub Date : 2020-09-09
    Jacopo Tani; Andrea F. Daniele; Gianmarco Bernasconi; Amaury Camus; Aleksandar Petrov; Anthony Courchesne; Bhairav Mehta; Rohit Suri; Tomasz Zaluska; Matthew R. Walter; Emilio Frazzoli; Liam Paull; Andrea Censi

    As robotics matures and increases in complexity, it is more necessary than ever that robot autonomy research be reproducible. Compared to other sciences, there are specific challenges to benchmarking autonomy, such as the complexity of the software stacks, the variability of the hardware and the reliance on data-driven techniques, amongst others. In this paper, we describe a new concept for reproducible

    更新日期:2020-09-10
  • SEAN: Social Environment for Autonomous Navigation
    arXiv.cs.RO Pub Date : 2020-09-09
    Nathan Tsoi; Mohamed Hussein; Jeacy Espinoza; Xavier Ruiz; Marynel Vázquez

    Social navigation research is performed on a variety of robotic platforms, scenarios, and environments. Making comparisons between navigation algorithms is challenging because of the effort involved in building these systems and the diversity of platforms used by the community; nonetheless, evaluation is critical to understanding progress in the field. In a step towards reproducible evaluation of social

    更新日期:2020-09-10
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