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  • A learning-based harmonic mapping: Framework, assessment, and case study of human-to-robot hand pose mapping
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-19
    Eunsuk Chong; Lionel Zhang; Veronica J. Santos

    Harmonic mapping provides a natural way of mapping two manifolds by minimizing distortion induced by the mapping. However, most applications are limited to mapping between 2D and/or 3D spaces owing to the high computational cost. We propose a novel approach, the harmonic autoencoder (HAE), by approximating a harmonic mapping in a data-driven way. The HAE learns a mapping from an input domain to a target

  • Hybrid conditional planning for robotic applications
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-19
    Ahmed Nouman; Volkan Patoglu; Esra Erdem

    Robots who have partial observability of and incomplete knowledge about their environments may have to consider contingencies while planning, and thus necessitate cognitive abilities beyond classical planning. Moreover, during planning, they need to consider continuous feasibility checks for executability of the plans in the real world. Conditional planning is concerned with reaching goals from an

  • Editorial
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-14
    Antonio Bicchi; Oliver Brock

    Soft manipulation fundamentally differs from traditional approaches to robotic manipulation and, as a result, much of the established wisdom of traditional manipulation must be questioned. Of course, most of the past results remain valid and form a conceptual basis for soft manipulation, but this basis must be partially revised and extended significantly to fully leverage the power of soft manipulation

  • Integrity monitoring for Kalman filter-based localization
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-08
    Guillermo Duenas Arana; Osama Abdul Hafez; Mathieu Joerger; Matthew Spenko

    The problem of quantifying robot localization safety in the presence of undetected sensor faults is critical when preparing for future applications where robots may interact with humans in life-critical situations; however, the topic is only sparsely addressed in the robotics literature. In response, this work leverages prior work in aviation integrity monitoring to tackle the more challenging case

  • ISER 2018 Editorial
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-05
    Jing Xiao; Torsten Kröger; Oussama Khatib

    This special issue presents significantly expanded articles based on selected contributions from the International Symposium on Experimental Robotics (ISER 2018), held during November 5–8, 2018 in Buenos Aires, Argentina. This is the 16th symposium of the ISER, a series of biennial international symposia. Sponsored by the International Foundation of Robotics Research (IFRR), the goal of ISER symposia

  • PAC-Bayes control: learning policies that provably generalize to novel environments
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-03
    Anirudha Majumdar; Alec Farid; Anoopkumar Sonar

    Our goal is to learn control policies for robots that provably generalize well to novel environments given a dataset of example environments. The key technical idea behind our approach is to leverage tools from generalization theory in machine learning by exploiting a precise analogy (which we present in the form of a reduction) between generalization of control policies to novel environments and generalization

  • Multimodal interaction-aware motion prediction for autonomous street crossing
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-10-01
    Noha Radwan; Wolfram Burgard; Abhinav Valada

    For mobile robots navigating on sidewalks, the ability to safely cross street intersections is essential. Most existing approaches rely on the recognition of the traffic light signal to make an informed crossing decision. Although these approaches have been crucial enablers for urban navigation, the capabilities of robots employing such approaches are still limited to navigating only on streets that

  • Ford Multi-AV Seasonal Dataset
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-09-30
    Siddharth Agarwal; Ankit Vora; Gaurav Pandey; Wayne Williams; Helen Kourous; James McBride

    This article presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles (AVs) at different days and times during 2017–2018. The vehicles traversed an average route of 66 km in Michigan that included a mix of driving scenarios such as the Detroit airport, freeways, city centers, university campus, and suburban neighborhoods. Each vehicle used in this data collection

  • Decentralized Multi-agent information-theoretic control for target estimation and localization: finding gas leaks
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-09-21
    Joseph R Bourne; Matthew N Goodell; Xiang He; Jake A Steiner; Kam K Leang

    This article presents a new decentralized multi-agent information-theoretic (DeMAIT) control algorithm for mobile sensors (agents). The algorithm leverages Bayesian estimation and information-theoretic motion planning for efficient and effective estimation and localization of a target, such as a chemical gas leak. The algorithm consists of: (1) a non-parametric Bayesian estimator, (2) an information-theoretic

  • Combining learned and analytical models for predicting action effects from sensory data
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-09-12
    Alina Kloss; Stefan Schaal; Jeannette Bohg

    One of the most basic skills a robot should possess is predicting the effect of physical interactions with objects in the environment. This enables optimal action selection to reach a certain goal state. Traditionally, dynamics are approximated by physics-based analytical models. These models rely on specific state representations that may be hard to obtain from raw sensory data, especially if no knowledge

  • Deep neural networks as add-on modules for enhancing robot performance in impromptu trajectory tracking
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-09-11
    Siqi Zhou; Mohamed K Helwa; Angela P Schoellig

    High-accuracy trajectory tracking is critical to many robotic applications, including search and rescue, advanced manufacturing, and industrial inspection, to name a few. Yet the unmodeled dynamics and parametric uncertainties of operating in such complex environments make it difficult to design controllers that are capable of accurately tracking arbitrary, feasible trajectories from the first attempt

  • Contact-space resolution model for a physically consistent view of simultaneous collisions in articulated-body systems: theory and experimental results
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-09-11
    Shameek Ganguly; Oussama Khatib

    Multi-surface interactions occur frequently in articulated-rigid-body systems such as robotic manipulators. Real-time prediction of contact-interaction forces is challenging for systems with many degrees of freedom (DOFs) because joint and contact constraints must be enforced simultaneously. While several contact models exist for systems of free rigid bodies, fewer models are available for articulated-body

  • A resource-aware approach to collaborative loop-closure detection with provable performance guarantees
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-09-01
    Yulun Tian; Kasra Khosoussi; Jonathan P How

    This paper presents resource-aware algorithms for distributed inter-robot loop-closure detection for applications such as collaborative simultaneous localization and mapping (CSLAM) and distributed image retrieval. In real-world scenarios, this process is resource-intensive as it involves exchanging many observations and geometrically verifying a large number of potential matches. This poses severe

  • Bridging the gap between safety and real-time performance in receding-horizon trajectory design for mobile robots
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-30
    Shreyas Kousik; Sean Vaskov; Fan Bu; Matthew Johnson-Roberson; Ram Vasudevan

    To operate with limited sensor horizons in unpredictable environments, autonomous robots use a receding-horizon strategy to plan trajectories, wherein they execute a short plan while creating the next plan. However, creating safe, dynamically feasible trajectories in real time is challenging, and planners must ensure persistent feasibility, meaning a new trajectory is always available before the previous

  • Learning stabilizable nonlinear dynamics with contraction-based regularization
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-30
    Sumeet Singh; Spencer M Richards; Vikas Sindhwani; Jean-Jacques E Slotine; Marco Pavone

    We propose a novel framework for learning stabilizable nonlinear dynamical systems for continuous control tasks in robotics. The key contribution is a control-theoretic regularizer for dynamics fitting rooted in the notion of stabilizability, a constraint which guarantees the existence of robust tracking controllers for arbitrary open-loop trajectories generated with the learned system. Leveraging

  • On the motion/stiffness decoupling property of articulated soft robots with application to model-free torque iterative learning control
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-28
    Riccardo Mengacci; Franco Angelini; Manuel G Catalano; Giorgio Grioli; Antonio Bicchi; Manolo Garabini

    This article tackles the problem of controlling articulated soft robots (ASRs), i.e., robots with either fixed or variable elasticity lumped at the joints. Classic control schemes rely on high-authority feedback actions, which have the drawback of altering the desired robot softness. The problem of accurate control of ASRs, without altering their inherent stiffness, is particularly challenging because

  • Geometry-aware manipulability learning, tracking, and transfer
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-24
    Noémie Jaquier; Leonel Rozo; Darwin G Caldwell; Sylvain Calinon

    Body posture influences human and robot performance in manipulation tasks, as appropriate poses facilitate motion or the exertion of force along different axes. In robotics, manipulability ellipsoids arise as a powerful descriptor to analyze, control, and design the robot dexterity as a function of the articulatory joint configuration. This descriptor can be designed according to different task requirements

  • Compliant gripper design, prototyping, and modeling using screw theory formulation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-24
    Irfan Hussain; Monica Malvezzi; Dongming Gan; Zubair Iqbal; Lakmal Seneviratne; Domenico Prattichizzo; Federico Renda

    This article investigates some aspects related to the design, modeling, prototyping, and testing of soft–rigid tendon-driven grippers. As a case study, we present the design and development of a two-finger soft gripper and exploit it as an example to demonstrate the application scenario of our mathematical model based on screw theory. A mathematical formulation based on screw theory is then presented

  • On infusing reachability-based safety assurance within planning frameworks for human–robot vehicle interactions
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-24
    Karen Leung; Edward Schmerling; Mengxuan Zhang; Mo Chen; John Talbot; J Christian Gerdes; Marco Pavone

    Action anticipation, intent prediction, and proactive behavior are all desirable characteristics for autonomous driving policies in interactive scenarios. Paramount, however, is ensuring safety on the road: a key challenge in doing so is accounting for uncertainty in human driver actions without unduly impacting planner performance. This article introduces a minimally interventional safety controller

  • Scaling simulation-to-real transfer by learning a latent space of robot skills
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-21
    Ryan C Julian; Eric Heiden; Zhanpeng He; Hejia Zhang; Stefan Schaal; Joseph J Lim; Gaurav S Sukhatme; Karol Hausman

    We present a strategy for simulation-to-real transfer, which builds on recent advances in robot skill decomposition. Rather than focusing on minimizing the simulation–reality gap, we propose a method for increasing the sample efficiency and robustness of existing simulation-to-real approaches which exploits hierarchy and online adaptation. Instead of learning a unique policy for each desired robotic

  • Hand closure model for planning top grasps with soft robotic hands
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-10
    Maria Pozzi; Sara Marullo; Gionata Salvietti; Joao Bimbo; Monica Malvezzi; Domenico Prattichizzo

    Automating the act of grasping is one of the most compelling challenges in robotics. In recent times, a major trend has gained the attention of the robotic grasping community: soft manipulation. Along with the design of intrinsically soft robotic hands, it is important to devise grasp planning strategies that can take into account the hand characteristics, but are general enough to be applied to different

  • Design and optimal control of a tiltrotor micro-aerial vehicle for efficient omnidirectional flight
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-06
    Mike Allenspach; Karen Bodie; Maximilian Brunner; Luca Rinsoz; Zachary Taylor; Mina Kamel; Roland Siegwart; Juan Nieto

    Omnidirectional micro-aerial vehicles (MAVs) are a growing field of research, with demonstrated advantages for aerial interaction and uninhibited observation. While systems with complete pose omnidirectionality and high hover efficiency have been developed independently, a robust system that combines the two has not been demonstrated to date. This paper presents the design and optimal control of a

  • Three-dimensional independent control of multiple magnetic microrobots via inter-agent forces
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-05
    Mohammad Salehizadeh; Eric Diller

    This article presents a method to independently control the position of multiple microscale magnetic robots in three dimensions, operating in close proximity to each other. Having multiple magnetic microrobots work together in close proximity is difficult due to magnetic interactions between the robots, and here we aim to control those interactions for the creation of desired multi-agent formations

  • Fast deep swept volume estimator
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-08-02
    Hao-Tien Lewis Chiang; John EG Baxter; Satomi Sugaya; Mohammad R Yousefi; Aleksandra Faust; Lydia Tapia

    Despite decades of research on efficient swept volume computation for robotics, computing the exact swept volume is intractable and approximate swept volume algorithms have been computationally prohibitive for applications such as motion and task planning. In this work, we employ deep neural networks (DNNs) for fast swept volume estimation. Since swept volume is a property of robot kinematics, a DNN

  • Exactly sparse Gaussian variational inference with application to derivative-free batch nonlinear state estimation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-29
    Timothy D Barfoot; James R Forbes; David J Yoon

    We present a Gaussian variational inference (GVI) technique that can be applied to large-scale nonlinear batch state estimation problems. The main contribution is to show how to fit both the mean and (inverse) covariance of a Gaussian to the posterior efficiently, by exploiting factorization of the joint likelihood of the state and data, as is common in practical problems. This is different than maximum

  • Robust and efficient forward, differential, and inverse kinematics using dual quaternions
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-20
    Neil T Dantam

    Modern approaches for robot kinematics employ the product of exponentials formulation, represented using homogeneous transformation matrices. Quaternions over dual numbers are an established alternative representation; however, their use presents certain challenges: the dual quaternion exponential and logarithm contain a zero-angle singularity, and many common operations are less efficient using dual

  • An obstacle disturbance selection framework: emergent robot steady states under repeated collisions
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-20
    Feifei Qian; Daniel E Koditschek

    Natural environments are often filled with obstacles and disturbances. Traditional navigation and planning approaches normally depend on finding a traversable “free space” for robots to avoid unexpected contact or collision. We hypothesize that with a better understanding of the robot–obstacle interactions, these collisions and disturbances can be exploited as opportunities to improve robot locomotion

  • HyP-DESPOT: A hybrid parallel algorithm for online planning under uncertainty
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-20
    Panpan Cai; Yuanfu Luo; David Hsu; Wee Sun Lee

    Robust planning under uncertainty is critical for robots in uncertain, dynamic environments, but incurs high computational cost. State-of-the-art online search algorithms, such as DESPOT, have vastly improved the computational efficiency of planning under uncertainty and made it a valuable tool for robotics in practice. This work takes one step further by leveraging both CPU and GPU parallelization

  • Large-scale outdoor scene reconstruction and correction with vision
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-15
    Michael Tanner; Pedro Piniés; Lina María Paz; Ştefan Săftescu; Alex Bewley; Emil Jonasson; Paul Newman

    We provide the theory and the system needed to create large-scale dense reconstructions for mobile-robotics applications: this stands in contrast to the object-centric reconstructions dominant in the literature. Our BOR2G system fuses data from multiple sensor modalities (cameras, lidars, or both) and regularizes the resulting 3D model. We use a compressed 3D data structure, which allows us to operate

  • Modeling biomechanical interaction between soft tissue and soft robotic instruments: importance of constitutive anisotropic hyperelastic formulations
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-14
    Emanuele Vignali; Emanuele Gasparotti; Katia Capellini; Benigno Marco Fanni; Luigi Landini; Vincenzo Positano; Simona Celi

    Cardiovascular diseases are the leading cause of death in the western countries. Robotic surgery recently emerged as a confirmed strategy in the cardiovascular field, especially thanks to the improvement of soft robotics. These techniques have demonstrated their potential in terms of speed of execution and precision. In this context, a deeper knowledge of the material properties of the blood vessels

  • The UMA-VI dataset: Visual–inertial odometry in low-textured and dynamic illumination environments
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-10
    David Zuñiga-Noël; Alberto Jaenal; Ruben Gomez-Ojeda; Javier Gonzalez-Jimenez

    This article presents a visual–inertial dataset gathered in indoor and outdoor scenarios with a handheld custom sensor rig, for over 80 min in total. The dataset contains hardware-synchronized data from a commercial stereo camera (Bumblebee®2), a custom stereo rig, and an inertial measurement unit. The most distinctive feature of this dataset is the strong presence of low-textured environments and

  • Video dataset of human demonstrations of folding clothing for robotic folding
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-10
    Andreas Verleysen; Matthijs Biondina; Francis wyffels

    General-purpose clothes-folding robots do not yet exist owing to the deformable nature of textiles, making it hard to engineer manipulation pipelines or learn this task. In order to accelerate research for the learning of the robotic clothes-folding task, we introduce a video dataset of human folding demonstrations. In total, we provide 8.5 hours of demonstrations from multiple perspectives leading

  • A soft manipulator for efficient delicate grasping in shallow water: Modeling, control, and real-world experiments
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-07
    Zheyuan Gong; Xi Fang; Xingyu Chen; Jiahui Cheng; Zhexin Xie; Jiaqi Liu; Bohan Chen; Hui Yang; Shihan Kong; Yufei Hao; Tianmiao Wang; Junzhi Yu; Li Wen

    Collecting in shallow water (water depth: ~30 m) is an emerging field that requires robotics for replacing human divers. Soft robots have several promising features (e.g., safe interaction with the environments, lightweight, etc.) for performing such tasks. In this article, we developed an underwater robotic system with a three-degree-of-freedom (3-DoF) soft manipulator for spatial delicate grasping

  • Large-scale, real-time visual–inertial localization revisited
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-07
    Simon Lynen; Bernhard Zeisl; Dror Aiger; Michael Bosse; Joel Hesch; Marc Pollefeys; Roland Siegwart; Torsten Sattler

    The overarching goals in image-based localization are scale, robustness, and speed. In recent years, approaches based on local features and sparse 3D point-cloud models have both dominated the benchmarks and seen successful real-world deployment. They enable applications ranging from robot navigation, autonomous driving, virtual and augmented reality to device geo-localization. Recently, end-to-end

  • Free space of rigid objects: caging, path non-existence, and narrow passage detection
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-07-07
    Anastasiia Varava; J. Frederico Carvalho; Danica Kragic; Florian T. Pokorny

    In this work, we propose algorithms to explicitly construct a conservative estimate of the configuration spaces of rigid objects in two and three dimensions. Our approach is able to detect compact path components and narrow passages in configuration space which are important for applications in robotic manipulation and path planning. Moreover, as we demonstrate, they are also applicable to identification

  • Image-based estimation, planning, and control for high-speed flying through multiple openings
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-27
    Dejun Guo; Kam K Leang

    This article focuses on enabling an aerial robot to fly through multiple openings at high speed using image-based estimation, planning, and control. State-of-the-art approaches assume that the robot’s global translational variables (e.g., position and velocity) can either be measured directly with external localization sensors or estimated onboard. Unfortunately, estimating the translational variables

  • Quasi-static analysis of planar sliding using friction patches
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-24
    M. Mahdi Ghazaei Ardakani; Joao Bimbo; Domenico Prattichizzo

    Flat objects lying on a surface are hard to grasp, but could be manipulated by sliding along the surface in a non-prehensile manner. This strategy is commonly employed by humans as pre-manipulation, for example to bring a cell phone to the edge of a table to pick it up. To endow robots with a similar capability, we introduce a mathematical model of planar sliding by means of a soft finger. The model

  • Search and rescue under the forest canopy using multiple UAVs
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-24
    Yulun Tian; Katherine Liu; Kyel Ok; Loc Tran; Danette Allen; Nicholas Roy; Jonathan P. How

    We present a multi-robot system for GPS-denied search and rescue under the forest canopy. Forests are particularly challenging environments for collaborative exploration and mapping, in large part due to the existence of severe perceptual aliasing which hinders reliable loop closure detection for mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) that perform

  • Relative multiplicative extended Kalman filter for observable GPS-denied navigation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-23
    Daniel P Koch; David O Wheeler; Randal W Beard; Timothy W McLain; Kevin M Brink

    This work presents a multiplicative extended Kalman filter (MEKF) for estimating the relative state of a multirotor vehicle operating in a GPS-denied environment. The filter fuses data from an inertial measurement unit and altimeter with relative-pose updates from a keyframe-based visual odometry or laser scan-matching algorithm. Because the global position and heading states of the vehicle are unobservable

  • Manipulating deformable objects by interleaving prediction, planning, and control
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-19
    Dale McConachie; Andrew Dobson; Mengyao Ruan; Dmitry Berenson

    We present a framework for deformable object manipulation that interleaves planning and control, enabling complex manipulation tasks without relying on high-fidelity modeling or simulation. The key question we address is when should we use planning and when should we use control to achieve the task? Planners are designed to find paths through complex configuration spaces, but for highly underactuated

  • Task-based hybrid shared control for training through forceful interaction
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-16
    Kathleen Fitzsimons; Aleksandra Kalinowska; Julius P Dewald; Todd D Murphey

    Despite the fact that robotic platforms can provide both consistent practice and objective assessments of users over the course of their training, there are relatively few instances where physical human–robot interaction has been significantly more effective than unassisted practice or human-mediated training. This article describes a hybrid shared control robot, which enhances task learning through

  • Dynamic locomotion for passive-ankle biped robots and humanoids using whole-body locomotion control
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-10
    Donghyun Kim; Steven Jens Jorgensen; Jaemin Lee; Junhyeok Ahn; Jianwen Luo; Luis Sentis

    Whole-body control (WBC) is a generic task-oriented control method for feedback control of loco-manipulation behaviors in humanoid robots. The combination of WBC and model-based walking controllers has been widely utilized in various humanoid robots. However, to date, the WBC method has not been employed for unsupported passive-ankle dynamic locomotion. As such, in this article, we devise a new WBC

  • Data-driven Koopman operators for model-based shared control of human–machine systems
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-10
    Alexander Broad; Ian Abraham; Todd Murphey; Brenna Argall

    We present a data-driven shared control algorithm that can be used to improve a human operator’s control of complex dynamic machines and achieve tasks that would otherwise be challenging, or impossible, for the user on their own. Our method assumes no a priori knowledge of the system dynamics. Instead, both the dynamics and information about the user’s interaction are learned from observation through

  • FSMI: Fast computation of Shannon mutual information for information-theoretic mapping
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-10
    Zhengdong Zhang; Theia Henderson; Sertac Karaman; Vivienne Sze

    Exploration tasks are embedded in many robotics applications, such as search and rescue and space exploration. Information-based exploration algorithms aim to find the most informative trajectories by maximizing an information-theoretic metric, such as the mutual information between the map and potential future measurements. Unfortunately, most existing information-based exploration algorithms are

  • PanoraMIS: An ultra-wide field of view image dataset for vision-based robot-motion estimation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-09
    Houssem-Eddine Benseddik; Fabio Morbidi; Guillaume Caron

    This article presents a new dataset of ultra-wide field of view images with accurate ground truth, called PanoraMIS. The dataset covers a large spectrum of panoramic cameras (catadioptric, twin-fisheye), robotic platforms (wheeled, aerial, and industrial robots), and testing environments (indoors and outdoors), and it is well suited to rigorously validate novel image-based robot-motion estimation algorithms

  • Human motion trajectory prediction: a survey
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-07
    Andrey Rudenko; Luigi Palmieri; Michael Herman; Kris M Kitani; Dariu M Gavrila; Kai O Arras

    With growing numbers of intelligent autonomous systems in human environments, the ability of such systems to perceive, understand, and anticipate human behavior becomes increasingly important. Specifically, predicting future positions of dynamic agents and planning considering such predictions are key tasks for self-driving vehicles, service robots, and advanced surveillance systems. This article provides

  • Distributed and consistent multi-image feature matching via QuickMatch
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-05
    Zachary Serlin; Guang Yang; Brandon Sookraj; Calin Belta; Roberto Tron

    In this work, we consider the multi-image object matching problem in distributed networks of robots. Multi-image feature matching is a keystone of many applications, including Simultaneous Localization and Mapping, homography, object detection, and Structure from Motion. We first review the QuickMatch algorithm for multi-image feature matching. We then present NetMatch, an algorithm for distributing

  • Multimodal estimation and communication of latent semantic knowledge for robust execution of robot instructions
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-05
    Jacob Arkin; Daehyung Park; Subhro Roy; Matthew R Walter; Nicholas Roy; Thomas M Howard; Rohan Paul

    The goal of this article is to enable robots to perform robust task execution following human instructions in partially observable environments. A robot’s ability to interpret and execute commands is fundamentally tied to its semantic world knowledge. Commonly, robots use exteroceptive sensors, such as cameras or LiDAR, to detect entities in the workspace and infer their visual properties and spatial

  • Multimodal trajectory optimization for motion planning
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-04
    Takayuki Osa

    Existing motion planning methods often have two drawbacks: (1) goal configurations need to be specified by a user, and (2) only a single solution is generated under a given condition. In practice, multiple possible goal configurations exist to achieve a task. Although the choice of the goal configuration significantly affects the quality of the resulting trajectory, it is not trivial for a user to

  • Reactive sampling-based path planning with temporal logic specifications
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-04
    Cristian Ioan Vasile; Xiao Li; Calin Belta

    We develop a sampling-based motion planning algorithm that combines long-term temporal logic goals with short-term reactive requirements. The mission specification has two parts: (1) a global specification given as a linear temporal logic (LTL) formula over a set of static service requests that occur at the regions of a known environment, and (2) a local specification that requires servicing a set

  • Design and characterization of a hybrid soft gripper with active palm pose control
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-06-01
    Vignesh Subramaniam; Snehal Jain; Jai Agarwal; Pablo Valdivia y Alvarado

    The design and characterization of a soft gripper with an active palm to control grasp postures is presented herein. The gripper structure is a hybrid of soft and stiff components to facilitate integration with traditional arm manipulators. Three fingers and a palm constitute the gripper, all of which are vacuum actuated. Internal wedges are used to tailor the deformation of a soft outer reinforced

  • The effects of reduced-gravity on planetary rover mobility
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-05-31
    Parna Niksirat; Adriana Daca; Krzysztof Skonieczny

    One of the major challenges faced by planetary exploration rovers today is the negotiation of difficult terrain, such as fine granular regolith commonly found on the Moon and Mars. Current testing methods on Earth fail to account for the effect of reduced gravity on the soil itself. This work characterizes the effects of reduced gravity on wheel–soil interactions between an ExoMars rover wheel prototype

  • Distributed multi-robot collision avoidance via deep reinforcement learning for navigation in complex scenarios
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-05-31
    Tingxiang Fan; Pinxin Long; Wenxi Liu; Jia Pan

    Developing a safe and efficient collision-avoidance policy for multiple robots is challenging in the decentralized scenarios where each robot generates its paths with limited observation of other robots’ states and intentions. Prior distributed multi-robot collision-avoidance systems often require frequent inter-robot communication or agent-level features to plan a local collision-free action, which

  • Control of ATRIAS in three dimensions: Walking as a forced-oscillation problem
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-05-31
    Siavash Rezazadeh; Jonathan W Hurst

    In this article, we present a new controller for stable and robust walking control of ATRIAS, an underactuated bipedal robot designed based on the spring-loaded inverted pendulum (SLIP) model. We propose a forced-oscillation scheme for control of vertical motion, which we prove to be stable and contractive. Moreover, we prove that, through some mild assumptions, the dynamics of the system can be written

  • Adaptive fovea for scanning depth sensors
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-05-21
    Zaid Tasneem; Charuvahan Adhivarahan; Dingkang Wang; Huikai Xie; Karthik Dantu; Sanjeev J Koppal

    Depth sensors have been used extensively for perception in robotics. Typically these sensors have a fixed angular resolution and field of view (FOV). This is in contrast to human perception, which involves foveating: scanning with the eyes’ highest angular resolution over regions of interest (ROIs). We build a scanning depth sensor that can control its angular resolution over the FOV. This opens up

  • Reactive planar non-prehensile manipulation with hybrid model predictive control
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-05-11
    Francois R Hogan; Alberto Rodriguez

    This article presents an offline solution and online approximation to the hybrid control problem of planar non-prehensile manipulation. Hybrid dynamics and underactuation are key characteristics of this task that complicate the design of feedback controllers. We show that a model predictive control approach used in tandem with integer programming offers a powerful solution to capture the dynamic constraints

  • Comparing model-based control methods for simultaneous stiffness and position control of inflatable soft robots
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-05-08
    Charles M. Best; Levi Rupert; Marc D. Killpack

    Inflatable robots are naturally lightweight and compliant, which may make them well suited for operating in unstructured environments or in close proximity to people. The inflatable joints used in this article consist of a strong fabric exterior that constrains two opposing compliant air bladders that generate torque (unlike McKibben actuators where pressure changes cause translation). This antagonistic

  • A temporal logic optimal controlsynthesis algorithm for large-scale multi-robot systems
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-04-29
    Yiannis Kantaros; Michael M Zavlanos

    This article proposes a new highly scalable and asymptotically optimal control synthesis algorithm from linear temporal logic specifications, called STyLuS* for large-Scale optimal Temporal Logic Synthesis, that is designed to solve complex temporal planning problems in large-scale multi-robot systems. Existing planning approaches with temporal logic specifications rely on graph search techniques applied

  • Vision and Wi-Fi fusion in probabilistic appearance-based localization
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-04-27
    Mathieu Nowakowski; Cyril Joly; Sébastien Dalibard; Nicolas Garcia; Fabien Moutarde

    This article introduces an indoor topological localization algorithm that uses vision and Wi-Fi signals. Its main contribution is a novel way of merging data from these sensors. The designed system does not require knowledge of the building plan or the positions of the Wi-Fi access points. By making the Wi-Fi signature suited to the FABMAP algorithm, this work develops an early fusion framework that

  • Design, implementation, and control of a deformable manipulator robot based on a compliant spine
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-04-13
    Thor Morales Bieze; Alexandre Kruszewski; Bruno Carrez; Christian Duriez

    This article presents the conception, the numerical modeling, and the control of a dexterous, deformable manipulator bio-inspired by the skeletal spine found in vertebrate animals. Through the implementation of this new manipulator, we show a methodology based on numerical models and simulations, that goes from design to control of continuum and soft robots. The manipulator is modeled using a finite

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