As an important approach to ensure safety and naturalness, compliant motion is already implemented in large-size robots, but it is still an undeveloped area in child-oriented robots as it calls for a lightweight and c...
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As an important approach to ensure safety and naturalness, compliant motion is already implemented in large-size robots, but it is still an undeveloped area in child-oriented robots as it calls for a lightweight and compact solution compared with large-size robots. In this paper, we proposed the design of a social robot which aims at conducting safe and playful Human-Robot Interaction (HRI), especially with children. We built a teddy bear robot prototype based on hybrid passive-active compliant system which consists of flexible joints as passive part and compliant motion controller as active part. The compliant controller detects external perturbation through motor state variables, therefore force and torque sensors could be omitted to keep overall system compact. Experiments conducted in typical HRI scenarios showed that the hybrid passive-active compliant system enabled our robot to conduct safer and more interactive physical interaction compared with robot under traditional control method.
While commercially available autonomous underwater vehicles (AUVs) are routinely used in survey missions, a new set of applications exist which clearly demand intervention capabilities: the maintenance of permanent un...
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ISBN:
(纸本)9781479969357
While commercially available autonomous underwater vehicles (AUVs) are routinely used in survey missions, a new set of applications exist which clearly demand intervention capabilities: the maintenance of permanent underwater structures as well as the recovery of benthic stations or black-boxes are a few of them. These tasks are addressed nowadays using manned submersibles or work-class remotely operated vehicles (ROVs), equipped with teleoperated arms under human supervision. In the context of the TRITON Spanish funded project, a subsea panel docking and an intervention procedure are proposed. The light-weight intervention AUV (I-AUV) Girona 500 is used to autonomously dock into a subsea panel using a funnel-based docking method for passive accommodation. Once docked, an autonomous fixed-based manipulation system, which uses feedback from a digital camera, is used to turn a valve and plug/unplug a connector. The paper presents the techniques used for the autonomous docking and manipulation as well as how the adapted subsea panel has been designed to facilitate such operations.
作者：
P. MorignotM. SouryC. LerouxH. VorobievaP. HedeCEA
LIST Interactive Robotics Laboratory B.P. 6 Fontenay aux Roses F-92265 France CEA
LIST Vision and Content Engineering Laboratory B.P. 6 Fontenay aux Roses F-92265 France
In this paper, we present a mobile robot with an arm and a gripper, which can generate its own scenarios before executing them. Hand-written scenarios, as we previously did, are not applicable any longer, since a wide...
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ISBN:
(纸本)9781424478149
In this paper, we present a mobile robot with an arm and a gripper, which can generate its own scenarios before executing them. Hand-written scenarios, as we previously did, are not applicable any longer, since a wider range of scenarios is aimed at, which cannot be predicted in advance. Our approach involves task planning, for scenario generation, and finite state automation, for scenario execution. Our robot is used for servicing handicapped or ageing persons in their apartment.
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from t...
International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really generate scientific progress? What are common and successful participation strategies? What makes a solution superior to a competing method? To address this gap in the literature, we performed a multicenter study with all 80 competitions that were conducted in the scope of IEEE ISBI 2021 and MICCAI 2021. Statistical analyses performed based on comprehensive descriptions of the submitted algorithms linked to their rank as well as the underlying participation strategies revealed common characteristics of winning solutions. These typically include the use of multi-task learning (63%) and/or multi-stage pipelines (61%), and a focus on augmentation (100%), image preprocessing (97%), data curation (79%), and post-processing (66%). The “typical” lead of a winning team is a computer scientist with a doctoral degree, five years of experience in biomedical image analysis, and four years of experience in deep learning. Two core general development strategies stood out for highly-ranked teams: the reflection of the metrics in the method design and the focus on analyzing and handling failure cases. According to the organizers, 43% of the winning algorithms exceeded the state of the art but only 11% completely solved the respective domain problem. The insights of our study could help researchers (1) improve algorithm development strategies when approaching new problems, and (2) focus on open research questions revealed by this work.
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