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  • 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

  • Modeling and analysis of soft robotic fingers using the fin ray effect
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-04-13
    Xiaowei Shan; Lionel Birglen

    Soft grasping of random objects in unstructured environments has been a research topic of predilection both in academia and in industry because of its complexity but great practical relevance. However, accurate modeling of soft hands and fingers has proven a difficult challenge to tackle. Focusing on this issue, this article presents a detailed mathematical modeling and performance analysis of parallel

  • Geometric constraint-based modeling and analysis of a novel continuum robot with Shape Memory Alloy initiated variable stiffness
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-04-13
    Chenghao Yang; Shineng Geng; Ian Walker; David T Branson; Jinguo Liu; Jian S Dai; Rongjie Kang

    Continuum robots exhibit promising adaptability and dexterity for soft manipulation due to their intrinsic compliance. However, this compliance may lead to challenges in modeling as well as positioning and loading. In this paper, a virtual work-based static model is established to describe the deformation and mechanics of continuum robots with a generic rod-driven structure, taking the geometric constraint

  • Simultaneous contact and aerodynamic force estimation (s-CAFE) for aerial robots
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-23
    Teodor Tomić; Philipp Lutz; Korbinian Schmid; Andrew Mathers; Sami Haddadin

    In this article, we consider the problem of multirotor flying robots physically interacting with the environment under influence of wind. The results are the first algorithms for simultaneous online estimation of contact and aerodynamic wrenches acting on the robot based on real-world data, without the need for dedicated sensors. For this purpose, we investigated two model-based techniques for discriminating

  • Robust navigation of a soft growing robot by exploiting contact with the environment
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-20
    Joseph D Greer; Laura H Blumenschein; Ron Alterovitz; Elliot W Hawkes; Allison M Okamura

    Navigation and motion control of a robot to a destination are tasks that have historically been performed with the assumption that contact with the environment is harmful. This makes sense for rigid-bodied robots, where obstacle collisions are fundamentally dangerous. However, because many soft robots have bodies that are low-inertia and compliant, obstacle contact is inherently safe. As a result,

  • Algebraic approach towards the exploitation of “softness”: the input–output equation for morphological computation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-20
    Mizuka Komatsu; Takaharu Yaguchi; Kohei Nakajima

    Recently, soft robots that consist of soft and deformable materials have received much attention for their adaptability to uncertain environments. Although these robots are difficult to control with a conventional control theory owing to their complex body dynamics, research from different perspectives attempts to actively exploit these body dynamics as an asset rather than a drawback. This approach

  • Energy-shaping control of soft continuum manipulators with in-plane disturbances
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-19
    Enrico Franco; Arnau Garriga-Casanovas

    Soft continuum manipulators offer levels of compliance and inherent safety that can render them a superior alternative to conventional rigid robots for a variety of tasks, such as medical interventions or human–robot interaction. However, the ability of soft continuum manipulators to compensate for external disturbances needs to be further enhanced to meet the stringent requirements of many practical

  • The Blackbird UAV dataset
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-18
    Amado Antonini; Winter Guerra; Varun Murali; Thomas Sayre-McCord; Sertac Karaman

    This article describes the Blackbird unmanned aerial vehicle (UAV) Dataset, a large-scale suite of sensor data and corresponding ground truth from a custom-built quadrotor platform equipped with an inertial measurement unit (IMU), rotor tachometers, and virtual color, grayscale, and depth cameras. Motivated by the increasing demand for agile, autonomous operation of aerial vehicles, this dataset is

  • Soft pneumatic actuator-driven origami-inspired modular robotic “pneumagami”
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-18
    Matthew A Robertson; Ozdemir Can Kara; Jamie Paik

    This article presents a new modular robotic platform for enabling reconfigurable, actively controlled, high-degree-of-freedom (high-DoF) systems with compact form factor. The robotic modules exploit the advantages of origami-inspired construction methods and materials, and soft pneumatic actuators (SPAs) to achieve an actuator embedded, parallel kinematic mechanism with three independently controlled

  • Underwater pre-touch based on artificial electric sense
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-18
    Frédéric Boyer; Vincent Lebastard; Steven Bruce Ferrer; Franck Geffard

    This article exploits a bio-inspired sensor technology named artificial electric-sense to emulate underwater pre-touch. The sensor is considered as an electric finger controlled remotely by an operator to follow the boundaries of objects. Using electric measurements only, the approach feeds back pre-touch forces and torques to the operator through an haptic interface. These forces and torques are generated

  • Improving user specifications for robot behavior through active preference learning: Framework and evaluation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-18
    Nils Wilde; Alexandru Blidaru; Stephen L Smith; Dana Kulić

    An important challenge in human–robot interaction (HRI) is enabling non-expert users to specify complex tasks for autonomous robots. Recently, active preference learning has been applied in HRI to interactively shape a robot’s behavior. We study a framework where users specify constraints on allowable robot movements on a graphical interface, yielding a robot task specification. However, users may

  • The Canadian Planetary Emulation Terrain Energy-Aware Rover Navigation Dataset
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-17
    Olivier Lamarre; Oliver Limoyo; Filip Marić; Jonathan Kelly

    Future exploratory missions to the Moon and to Mars will involve solar-powered rovers; careful vehicle energy management is critical to the success of such missions. This article describes a unique dataset gathered by a small, four-wheeled rover at a planetary analog test facility in Canada. The rover was equipped with a suite of sensors designed to enable the study of energy-aware navigation and path

  • Reliability analysis of a tendon-driven actuation for soft robots
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-13
    Useok Jeong; Keunsu Kim; Sang-Hun Kim; Hyunhee Choi; Byeng Dong Youn; Kyu-Jin Cho

    The reliability of soft robotic devices will be the bottleneck that slows their commercialization. In particular, fatigue failure issues are a major concern. Thus, reliability should be taken into account from the earliest stages of development. However, to date, there have been no attempts to analyze the reliability of soft robotic devices in a systematic manner. When soft robots are employed to force

  • Multi-segment soft robotic fingers enable robust precision grasping
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-13
    Clark B Teeple; Theodore N Koutros; Moritz A Graule; Robert J. Wood

    In this work, we discuss the design of soft robotic fingers for robust precision grasping. Through a conceptual analysis of the finger shape and compliance during grasping, we confirm that antipodal grasps are more stable when contact with the object occurs on the side of the fingers (i.e., pinch grasps) instead of the fingertips. In addition, we show that achieving such pinch grasps with soft fingers

  • Pressure distribution classification and segmentation of human hands in contact with the robot body
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-03-10
    Alessandro Albini; Giorgio Cannata

    Human–robot interaction (HRI) has the goal of making possible the cooperation between humans and robots, in order to exploit the strengths of both players to accomplish complex tasks, that are otherwise difficult to tackle, or tedious and error prone. Towards this aim, and in order to ensure safe interaction, robots are expected to embed human-like sensing modalities such as vision, touch, speech,

  • Model-free vision-based shaping of deformable plastic materials
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-02-25
    Andrea Cherubini; Valerio Ortenzi; Akansel Cosgun; Robert Lee; Peter Corke

    We address the problem of shaping deformable plastic materials using non-prehensile actions. Shaping plastic objects is challenging, because they are difficult to model and to track visually. We study this problem, by using kinetic sand, a plastic toy material that mimics the physical properties of wet sand. Inspired by a pilot study where humans shape kinetic sand, we define two types of actions:

  • Design and prototyping soft–rigid tendon-driven modular grippers using interpenetrating phase composites materials
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-02-25
    Irfan Hussain; Oraib Al-Ketan; Federico Renda; Monica Malvezzi; Domenico Prattichizzo; Lakmal Seneviratne; Rashid K Abu Al-Rub; Dongming Gan

    Advances in soft robotics and material science have enabled rapid progress in soft grippers. The ability to 3D print materials with softer, more elastic materials properties is a recent development and a key enabling technology for the rapid development of soft robots. However, obtaining the desired mechanical properties (e.g., stiffness) of the soft joints and information about the parameters to select

  • Automatically steering cardiac catheters in vivo with respiratory motion compensation
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-02-19
    Paul M Loschak; Alperen Degirmenci; Cory M Tschabrunn; Elad Anter; Robert D Howe

    A robotic system for automatically navigating ultrasound (US) imaging catheters can provide real-time intra-cardiac imaging for diagnosis and treatment while reducing the need for clinicians to perform manual catheter steering. Clinical deployment of such a system requires accurate navigation despite the presence of disturbances including cyclical physiological motions (e.g., respiration). In this

  • Special Issue on the 2018 Robotics: Science and Systems Conference
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-02-10
    Nikolay Atanasov; Chris Amato

    This editorial introduces a special issue for the Robotics: Science and Systems (RSS) conference in 2018. RSS 2018 took place on the campus of Carnegie Mellon University in Pittsburgh, PA, USA, from June 26 to 30 and showcased 71 original papers. This special issue presents a selection of 11 articles expanded and improved by the authors from their original form presented at the conference. These articles

  • Batch Informed Trees (BIT*): Informed asymptotically optimal anytime search
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-01-27
    Jonathan D Gammell; Timothy D Barfoot; Siddhartha S Srinivasa

    Path planning in robotics often requires finding high-quality solutions to continuously valued and/or high-dimensional problems. These problems are challenging and most planning algorithms instead solve simplified approximations. Popular approximations include graphs and random samples, as used by informed graph-based searches and anytime sampling-based planners, respectively. Informed graph-based

  • Human motion analysis in medical robotics via high-dimensional inverse reinforcement learning
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-01-29
    Kun Li; Joel W Burdick

    This work develops a novel high-dimensional inverse reinforcement learning (IRL) algorithm for human motion analysis in medical, clinical, and robotics applications. The method is based on the assumption that a surgical robot operators’ skill or a patient’s motor skill is encoded into the innate reward function during motion planning and recovered by an IRL algorithm from motion demonstrations. This

  • Locomotion of a multi-link non-holonomic snake robot with passive joints
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-01-27
    Tony Dear; Blake Buchanan; Rodrigo Abrajan-Guerrero; Scott David Kelly; Matthew Travers; Howie Choset

    Conventional approaches in prescribing controls for locomoting robots assume control over all input degrees of freedom (DOFs). Many robots, such as those with non-holonomic constraints, may not require or even allow for direct command over all DOFs. In particular, a snake robot with more than three links with non-holonomic constraints cannot achieve arbitrary configurations in all of its joints while

  • Controlling two-dimensional collective formation and cooperative behavior of magnetic microrobot swarms
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2020-01-28
    Xiaoguang Dong; Metin Sitti

    Magnetically actuated mobile microrobots can access distant, enclosed, and small spaces, such as inside microfluidic channels and the human body, making them appealing for minimally invasive tasks. Despite their simplicity when scaling down, creating collective microrobots that can work closely and cooperatively, as well as reconfigure their formations for different tasks, would significantly enhance

  • A scalable motion planner for high-dimensional kinematic systems
    Int. J. Robot. Res. (IF 4.703) Pub Date : 2019-12-17
    Ryan Luna; Mark Moll; Julia Badger; Lydia E Kavraki

    Sampling-based algorithms are known for their ability to effectively compute paths for high-dimensional robots in relatively short times. The same algorithms, however, are also notorious for poor-quality solution paths, particularly as the dimensionality of the system grows. This work proposes a new probabilistically complete sampling-based algorithm, XXL, specially designed to plan the motions of

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