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IEEE Robotics and Automation Society Information
Year: 2022 | Volume: 7 | Issue: 4
Peg-in-Hole Assembly With Dual-Arm Robot and Dexterous Robot Hands
Dong-Hyuk Lee;Myoung-Su Choi;Hyeonjun Park;Ga-Ram Jang;Jae-Han Park;Ji-Hun Bae
Publication Year: 2022,Page(s):8566 - 8573
Cited by: Papers (23)
This study focuses on implementing robotic peg-in-hole in a more human-like approach, namely using dual-arms and dexterous robotic hands. The peg-in-hole strategy in this study mainly consists of two parts: grasping strategy (hand part) and assembly strategy (arm part). The grasping strategy explains the fundamental grasping method called “advanced blind grasping” and the in-hand manipulation meth...Show More
Recommending Fine-Grained Tool Consistent With Common Sense Knowledge for Robot
Jianjia Xin;Lichun Wang;Shaofan Wang;Yukun Liu;Chao Yang;Baocai Yin
Publication Year: 2022,Page(s):8574 - 8581
Cited by: Papers (1)
When robots carry out task, selecting an appropriate tool is necessary. The current research ignores the fine-grained characteristic of tasks, and mainly focuses on whether the task can be completed. Little consideration is paid for the object being manipulated, which affects the task completion quality. In order to support task oriented fine-grained tool recommendation, based on common sense know...Show More
Robustness of Interaction Parameters Identification Technique for Collaborative Robots
Publication Year: 2022,Page(s):8582 - 8589
Cited by: Papers (2)
The work focuses on accuracy of the identification procedure allowing to estimate the force and its application point in human-robot physical interaction. It is assumed that the desired parameters are estimated using data obtained from internal torque sensors embedded in the robot joints as well as 3D geometric models describing the robot link surfaces. In practice, the measurement data are corrup...Show More
Robust Visual Teach and Repeat for UGVs Using 3D Semantic Maps
Publication Year: 2022,Page(s):8590 - 8597
Cited by: Papers (3)
We propose a Visual Teach and Repeat (VTR) algorithm using semantic landmarks extracted from environmental objects for ground robots with fixed mount monocular cameras. The proposed algorithm is robust to changes in the starting pose of the camera/robot, where a pose is defined as the planar position plus the orientation around the vertical axis. VTR consists of a teach phase in which a robot move...Show More
Using R-Functions to Control the Shape of Soft Robots
Publication Year: 2022,Page(s):8598 - 8603
Cited by: Papers (4)
In this letter, we introduce a new approach for soft robot shape formation and morphing using approximate distance fields. The method uses concepts from constructive solid geometry, R-functions, to construct an approximate distance function to the boundary of a domain in $\Re ^{d}$. The gradients of the R-functions can then be used to generate control algorithms for shape formation tasks for soft ...Show More
Optimized Dynamic Motion Performance for a 5-DoF Electromagnetic Manipulation
Publication Year: 2022,Page(s):8604 - 8610
Cited by: Papers (11)
High precision manipulation and optimization of actuation current are major concerns in the design of magnetic manipulation systems. In this paper, a flexible magnetic field mapping model has been employed to determine the field distribution of a compact electromagnetic manipulation system in 3D space, and validated by a high-resolution magnetic calibration system and Finite Element Analysis, whic...Show More
Learning Perceptual Locomotion on Uneven Terrains Using Sparse Visual Observations
Publication Year: 2022,Page(s):8611 - 8618
Cited by: Papers (4)
To proactively navigate and traverse various terrains, active use of visual perception becomes indispensable. We aim to investigate the feasibility and performance of using sparse visual observations to achieve perceptual locomotion over a range of common terrains (steps, ramps, gaps, and stairs) in human-centered environments. We formulate a selection of sparse visual inputs suitable for locomoti...Show More
EfficientGrasp: A Unified Data-Efficient Learning to Grasp Method for Multi-Fingered Robot Hands
Publication Year: 2022,Page(s):8619 - 8626
Cited by: Papers (17)
Autonomous grasping of novel objects that are previously unseen to a robot is an ongoing challenge in robotic manipulation. In the last decades, many approaches have been presented to address this problem for specific robot hands. The UniGrasp framework, introduced recently, has the ability to generalize to different types of robotic grippers; however, this method does not work on grippers with cl...Show More
A Framework for Optimized Topology Design and Leader Selection in Affine Formation Control
Publication Year: 2022,Page(s):8627 - 8634
Cited by: Papers (16)
This paper studies the problem of topology design and leader selection to activate affine formation control schemes. The affine formation control enjoys a distinguishing feature from other control methods in that the whole formation can be dynamically maneuvered by controlling a small number of agents called leaders. This relies on the stress matrix which defines the inter-agent communication/sens...Show More
Reconfigurable Self-Sensing Pneumatic Artificial Muscle With Locking Ability Based on Modular Multi-Chamber Soft Actuator
Publication Year: 2022,Page(s):8635 - 8642
Cited by: Papers (9)
In wearable applications, traditional pneumatic artificial muscles (PAMs) cannot fully satisfy the requirements of safe and sufficient interaction with the human body. The requirements include high contraction ratio, self-contained sensing, reconfiguration, locking abilities, and avoidance of the squeezing force acting on the human tissue. In this letter, a reconfigurable self-sensing pneumatic ar...Show More
Grasping Strategy for Unknown Objects Based on Real-Time Grasp-Stability Evaluation Using Proximity Sensing
Yosuke Suzuki;Ryoya Yoshida;Tokuo Tsuji;Toshihiro Nishimura;Tetsuyou Watanabe
Publication Year: 2022,Page(s):8643 - 8650
Cited by: Papers (6)
This letter proposes a robust grasping strategy for unknown objects by performing non-contact grasp-stability evaluation based on proximity sensing. First, we developed a proximity sensor for a multi-fingered hand. Its features are sensor mounting on a spherical fingertip and coating with transparent resin, which are advantageous for nearest point estimation and fingertip motion generation. Next, ...Show More
Exploring Event Camera-Based Odometry for Planetary Robots
Florian Mahlknecht;Daniel Gehrig;Jeremy Nash;Friedrich M. Rockenbauer;Benjamin Morrell;Jeff Delaune;Davide Scaramuzza
Publication Year: 2022,Page(s):8651 - 8658
Cited by: Papers (34)
Due to their resilience to motion blur and high robustness in low-light and high dynamic range conditions, event cameras are poised to become enabling sensors for vision-based exploration on future Mars helicopter missions. However, existing event-based visual-inertial odometry (VIO) algorithms either suffer from high tracking errors or are brittle, since they cannot cope with significant depth un...Show More
Design, Fabrication, and Characterization of a Hybrid Bionic Spherical Robotics With Multilegged Feedback Mechanism
Jiaxi Zheng;Peng Xu;Zhaochen Meng;Jianhua Liu;Siyuan Wang;Xinyu Wang;Guangming Xie;Jin Tao;Minyi Xu
Publication Year: 2022,Page(s):8659 - 8666
Cited by: Papers (6)
Spherical robots have many desirable traits when designing mass efficient systems interacted with unstructured terrain. In this letter, we propose a hybrid bionic spherical robot based on the morphological properties of sea urchins and the movement characteristics of tumbleweeds. This robot enables it to move freely in harsh terrain with the distributed high-aspect-ratio telescopic units, where ou...Show More
Neural Scene Representation for Locomotion on Structured Terrain
David Hoeller;Nikita Rudin;Christopher Choy;Animashree Anandkumar;Marco Hutter
Publication Year: 2022,Page(s):8667 - 8674
Cited by: Papers (16)
We propose a learning-based method to reconstruct the local terrain for locomotion with a mobile robot traversing urban environments. Using a stream of depth measurements from the onboard cameras and the robot’s trajectory, the algorithm estimates the topography in the robot’s vicinity. The raw measurements from these cameras are noisy and only provide partial and occluded observations that in man...Show More
Kinematics-Based Adaptive Assistance of a Semi-Passive Upper-Limb Exoskeleton for Workers in Static and Dynamic Tasks
Lorenzo Grazi;Emilio Trigili;Noemi Caloi;Giulia Ramella;Francesco Giovacchini;Nicola Vitiello;Simona Crea
Publication Year: 2022,Page(s):8675 - 8682
Cited by: Papers (15)
Typical industrial work activities may include a variety of different gestures, entailing the execution of dynamic and static movements. Occupational upper-limb exoskeletons can assist the shoulder complex in both static and dynamic gestures, but the required assistance level may be different according to the tasks. This article presents the design, development, and experimental evaluation of a no...Show More
Reduced Interface Models for Haptic Interfacing With Virtual Environments
Publication Year: 2022,Page(s):8683 - 8690
Cited by: Papers (1)
Haptic interfacing typically requires high communication frequencies in order to render realistic interactions between a user and a virtual environment. In this work, we introduce reduced interface modelling (RIM) as a method to bridge the discrepancy in frequency requirements between haptic devices and virtual environment simulators. The method offers a model-based approach to approximate the env...Show More
Reduced Interface Models for Haptic Interfacing With Virtual Environments
Year: 2022 | Volume: 7 | Issue: 4
Embodied Active Domain Adaptation for Semantic Segmentation via Informative Path Planning
René Zurbrügg;Hermann Blum;Cesar Cadena;Roland Siegwart;Lukas Schmid
Publication Year: 2022,Page(s):8691 - 8698
Cited by: Papers (11)
This work presents an embodied agent that can adapt its semantic segmentation network to new indoor environments in a fully autonomous way. Because semantic segmentation networks fail to generalize well to unseen environments, the agent collects images of the new environment which are then used for self-supervised domain adaptation. We formulate this as an informative path planning problem, and pr...Show More
Dynamic Task Scheduling for Human-Robot Collaboration
Publication Year: 2022,Page(s):8699 - 8704
Cited by: Papers (15)
In human-robot collaboration systems, the human-robot team works together to complete all tasks of the assigned job. Tasks’ precedence order is a factor that determines which task should be completed first. A human agent has an expected performance on each task, but the actual performance of the human agent on a task may differ from the expected performance at different times. Therefore, it is als...Show More
On the Design of Integrated Tele-Monitoring/ Operation System for Therapeutic Devices in Isolation Intensive Care Unit
ChangSeob Song;Gyungtak Yang;Sungwoo Park;Namseon Jang;Soobin Jeon;Sang-Rok Oh;Donghyun Hwang
Publication Year: 2022,Page(s):8705 - 8712
Cited by: Papers (3)
We design a central controller system (CCS) and a tele-controlled system (TCS) with an aim of developing the integrated tele-monitoring/operation system that can enable the medical staff to tele-monitor the state of therapeutic devices utilized in the isolation intensive care unit (ICU) and to tele-operate its user interfaces. To achieve this aim, we survey the medical staff for medical requiremen...Show More
Unsupervised Class-Agnostic Instance Segmentation of 3D LiDAR Data for Autonomous Vehicles
Lucas Nunes;Xieyuanli Chen;Rodrigo Marcuzzi;Aljosa Osep;Laura Leal-Taixé;Cyrill Stachniss;Jens Behley
Publication Year: 2022,Page(s):8713 - 8720
Cited by: Papers (11)
Fine-grained scene understanding is essential for autonomous driving. The context around a vehicle can change drastically while navigating, making it hard to identify and understand the different objects that may appear. Although recent efforts on semantic and panoptic segmentation pushed the field of scene understanding forward, it is still a challenging task. Current methods depend on annotation...Show More
Challenges of SLAM in Extremely Unstructured Environments: The DLR Planetary Stereo, Solid-State LiDAR, Inertial Dataset
Riccardo Giubilato;Wolfgang Stürzl;Armin Wedler;Rudolph Triebel
Publication Year: 2022,Page(s):8721 - 8728
Cited by: Papers (16)
We present the DLR Planetary Stereo, Solid-State LiDAR, Inertial (S3LI) dataset, recorded on Mt. Etna, Sicily, an environment analogous to the Moon and Mars, using a hand-held sensor suite with attributes suitable for implementation on a space-like mobile rover. The environment is characterized by challenging conditions regarding both the visual and structural appearance: severe visual aliasing po...Show More
Fully-Probabilistic Terrain Modelling and Localization With Stochastic Variational Gaussian Process Maps
Publication Year: 2022,Page(s):8729 - 8736
Cited by: Papers (4)
Gaussian processes (GPs) are becoming a standard tool to build terrain representations thanks to their capacity to model map uncertainty. This effectively yields a reliability measure of the areas of the map, which can be directly utilized by Bayes filtering algorithms in robot localization problems. A key factor is that this map uncertainty can incorporate the noise intrinsic to the terrain surve...Show More
EV-Catcher: High-Speed Object Catching Using Low-Latency Event-Based Neural Networks
Ziyun Wang;Fernando Cladera;Anthony Bisulco;Daewon Lee;Camillo J. Taylor;Kostas Daniilidis;M. Ani Hsieh;Daniel D. Lee;Volkan Isler
Publication Year: 2022,Page(s):8737 - 8744
Cited by: Papers (8)
Event-based sensors have recently drawn increasing interest in robotic perception due to their lower latency, higher dynamic range, and lower bandwidth requirements compared to standard CMOS-based imagers. These properties make them ideal tools for real-time perception tasks in highly dynamic environments. In this work, we demonstrate an application where event cameras excel: accurately estimating...Show More
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