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arXiv 2023年

作者： Li, Juncheng Cappelleri, David J. The Multi-Scale Robotics & Automation Lab School of Mechanical Engineering Purdue University West LafayetteIN United States

In this paper, we present Sim-MEES: a large-scale synthetic dataset that contains 1,550 objects with varying difficulty levels and physics properties, as well as 11 million grasp labels for mobile manipulators to plan grasps using different gripper modalities in cluttered environments. Our dataset generation process combines analytic models and dynamic simulations of the entire cluttered environment to provide accurate grasp labels. We provide a detailed study of our proposed labeling process for both parallel jaw grippers and suction cup grippers, comparing them with state-of-the-art methods to demonstrate how Sim-MEES can provide precise grasp labels in cluttered environments. Copyright © 2023, The Authors. All rights reserved.

关键词： Grippers

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Sim-Grasp: Learning 6-DOF Grasp Policies for Cluttered Environments Using a Synthetic Benchmark

arXiv

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arXiv 2024年

作者： Li, Juncheng Cappelleri, David J. The Multi-Scale Robotics & Automation Lab School of Mechanical Engineering Purdue University West LafayetteIN United States Purdue University West LafayetteIN United States

In this paper, we present Sim-Grasp, a robust 6-DOF two-finger grasping system that integrates advanced language models for enhanced object manipulation in cluttered environments. We introduce the Sim-Grasp-Dataset, which includes 1,550 objects across 500 scenarios with 7.9 million annotated labels, and develop Sim-GraspNet to generate grasp poses from point clouds. The Sim-Grasp-Polices achieve grasping success rates of 97.14% for single objects and 87.43% and 83.33% for mixed clutter scenarios of Levels 1-2 and Levels 3-4 objects, respectively. By incorporating language models for target identification through text and box prompts, Sim-Grasp enables both object-agnostic and target picking, pushing the boundaries of intelligent robotic systems. The codebase can be accessed at https://***/junchengli1/Sim-Grasp. Copyright © 2024, The Authors. All rights reserved.

关键词： Robot learning

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Design, Fabrication, and Characterization of a Helical multi-Material MicroRobot with a Detachable Payload (HMMR-DP)

Design, Fabrication, and Characterization of a Helical Multi...

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International Conference on Manipulation, automation and robotics at Small scales (MARSS)

作者： Yang Yang Liyuan Tan Aaron C. Davis David J. Cappelleri Multi-Scale Robotics and Automation Lab School of Mechanical En-gineering Purdue University West Lafayette IN USA Weldon School of Biomedical Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9798350376807

ISBN: (纸本)9798350376814

This paper employs a biodegradable hydrogel to create a Helical multi-Material MicroRobot with a Detachable Payload (HMMR-DP) capable of achieving for drug delivery applications. The biodegradability of the microstructures is as-sessed through experimentation at different concentrations and temperatures. The swimming capabilities of the microrobots are examined by experimental analysis using a rotating magnetic field.

关键词： Connectors Targeted drug delivery Hydrogels Hidden Markov models Tail Rigidity Microstructure

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Sim-Suction: Learning a Suction Grasp Policy for Cluttered Environments Using a Synthetic Benchmark

arXiv

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arXiv 2023年

作者： Li, Juncheng Cappelleri, David J. Multi-Scale Robotics & Automation Lab School of Mechanical Engineering Purdue University West LafayetteIN United States Purdue University West LafayetteIN United States

This paper presents Sim-Suction, a robust objectaware suction grasp policy for mobile manipulation platforms with dynamic camera viewpoints, designed to pick up unknown objects from cluttered environments. Suction grasp policies typically employ data-driven approaches, necessitating largescale, accurately-annotated suction grasp datasets. However, the generation of suction grasp datasets in cluttered environments remains underexplored, leaving uncertainties about the relationship between the object of interest and its surroundings. To address this, we propose a benchmark synthetic dataset, Sim- Suction-Dataset, comprising 500 cluttered environments with 3.2 million annotated suction grasp poses. The efficient Sim-Suction- Dataset generation process provides novel insights by combining analytical models with dynamic physical simulations to create fast and accurate suction grasp pose annotations. We introduce Sim-Suction-Pointnet to generate robust 6D suction grasp poses by learning point-wise affordances from the Sim-Suction-Dataset, leveraging the synergy of zero-shot text-to-segmentation. Realworld experiments for picking up all objects demonstrate that Sim-Suction-Pointnet achieves success rates of 96.76%, 94.23%, and 92.39% on cluttered level 1 objects (prismatic shape), cluttered level 2 objects (more complex geometry), and cluttered mixed objects, respectively. The codebase can be accessed at https://***/junchengli1/Sim-Suction-API. Copyright © 2023, The Authors. All rights reserved.

关键词： Zero-shot learning

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Pose-Estimate-Based Target Tracking for Human-Guided Remote Sensor Mounting with a UAV

Pose-Estimate-Based Target Tracking for Human-Guided Remote ...

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2020 IEEE International Conference on robotics and automation, ICRA 2020

作者： McArthur, Daniel R. An, Ze Cappelleri, David J. Purdue University Multi-Scale Robotics and Automation Lab School of Mechanical Engineering West LafayetteIN47907 United States

ISBN: (纸本)9781728173955

In this paper, we present a method for pose-estimate-based target tracking (PBTT) that enables the performance of autonomous aerial manipulation operations in unstructured environments using fully on-board computation for both UAV localization and target tracking. The PBTT method does not depend on extracting traditional visual features (e.g. using SIFT, SURF, ORB, etc.) on or near the target. Instead, the algorithm combines input from an RGB-D camera and the UAV's position estimator (which utilizes a downward-facing optical flow camera for horizontal localization) to track a target point selected by a human operator. The effectiveness of the PBTT method is evaluated through several autonomous flight tests performed with the Interacting-Boomcopter (I-BC) UAV platform in unstructured environments and in the presence of light wind disturbances. © 2020 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Pose-Estimate-Based Target Tracking for Human-Guided Remote Sensor Mounting with a UAV

Pose-Estimate-Based Target Tracking for Human-Guided Remote ...

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IEEE International Conference on robotics and automation (ICRA)

作者： Daniel R. McArthur Ze An David J. Cappelleri Multi-Scale Robotics and Automation Lab School of Mechanical Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9781728173955

ISBN: (纸本)9781728173962

关键词： Target tracking Cameras Unmanned aerial vehicles Visualization Task analysis Surface cleaning Three-dimensional displays

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Stiffness Characterization and Micromanipulation for Biomedical Applications using the Vision-based Force-Sensing Magnetic Mobile Microrobot

Stiffness Characterization and Micromanipulation for Biomedi...

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International Conference on Manipulation, automation and robotics at Small scales (MARSS)

作者： Georges Adam Mazin Hakim Luis Solorio David J. Cappelleri Multi-Scale Robotics and Automation Lab School of Mechanical Engineering Purdue University West Lafayette IN USA Weldon School of Biomedical Engineering Purdue University West Lafayette IN USA

ISBN: (数字)9781728193496

ISBN: (纸本)9781728193502

This paper presents the use of a micro-force sensing mobile microrobot (μFSMM) for in vitro biomedical applications. The μFSMM utilizes a vision-based force sensor end-effector, which computes the force based on the deflection of a compliant structure with a known stiffness using a computer vision tracking algorithm. The μFSMM is used to characterize the stiffness of several different alginate and hyaluronic acid hydrogel spheroid samples, which are typically used in 3D tissue engineered constructs for studying cellular behavior. Additionally, μFSMM is used to perform safe micromanipulation tasks with these spheroids. These experimental results showcase some of the applications of this unique microrobot design in the fields of mechanobiology, theranostics, and force-guided micromanipulation.

关键词： Robot sensing systems Sensors Robots Force Electronic countermeasures Biomedical measurement Three-dimensional displays

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Design of the I-BoomCopter UAV for environmental interaction

Design of the I-BoomCopter UAV for environmental interaction

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2017 IEEE International Conference on robotics and automation, ICRA 2017

作者： McArthur, Daniel R. Chowdhury, Arindam B. Cappelleri, David J. Multi-Scale Robotics and Automation Lab School of Mechanical Engineering Purdue University West LafayetteIN47907 United States

ISBN: (纸本)9781509046331

This paper presents the design of the Interacting-BoomCopter (I-BoomCopter) unmanned aerial vehicle (UAV), designed specifically for environmental interactions. The novel design consists of a horizontally mounted four-blade reversible propeller on a front boom that is attached to a standard tri-rotor UAV configuration. A custom end-effector and force sensor is placed at the end of the front boom for autonomous pushing and pulling interaction tasks. The modeling of the new platform is presented and two prototype versions built, flight tested, and characterized. Finally, the efficacy of the new platform for environmental interactions is evaluated with an autonomous door opening task and a teleoperated door opening and door closing task. © 2017 IEEE.

关键词： Antennas

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Design of the I-BoomCopter UAV for environmental interaction

Design of the I-BoomCopter UAV for environmental interaction

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IEEE International Conference on robotics and automation (ICRA)

作者： Daniel R. McArthur Arindam B. Chowdhury David J. Cappelleri Multi-Scale Robotics and Automation Lab Purdue University West Lafayette IN USA

关键词： Propellers Prototypes Rotors Unmanned aerial vehicles Acceleration Dynamics Force

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Artificial bacterial flagella functionalized with temperature-sensitive liposomes for biomedical applications

Artificial bacterial flagella functionalized with temperatur...

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2013 17th International Conference on Solid-State Sensors, Actuators and Microsystems, TRANSDUCERS and EUROSENSORS 2013

作者： Qiu, F. Mhanna, R. Zhang, L. Ding, Y. Sugihara, K. Zenobi-Wong, M. Nelson, B.J. Multi-Scale Robotics Lab ETH Zurich Zurich Switzerland Cartilage Engineering Regeneration ETH Zurich Zurich Switzerland Department of Mechanical and Automation Engineering Chinese University of Hong Kong Hong Kong Laboratory of Biosensors and Bioelectronics ETH Zurich Zurich Switzerland

ISBN: (纸本)9781467359818

Inspired by flagellar propulsion of bacterial such as E. coli, artificial bacterial flagella (ABFs) are magnetic swimming microrobots with helical shapes. ABFs can perform precise three-dimensional (3D) navigation in liquids under low-strength rotating magnetic fields making them attractive tools for drug delivery applications. Further functionalization of these swimming microrobots is necessary to optimize their performance of biomedical tasks. We report here for the first time the successful functionalization of titanium-coated ABFs with temperature-sensitive dipalmitoylphosphatidylcholine (DPPC) liposomes. Adsorption of intact liposomes on titanium was assessed using quartz crystal microbalance with dissipation monitoring (QCM-D). The adsorption of fluorescently labeled liposomes on the surface of ABFs was confirmed with confocal laser scanning microscopy (CLSM) images. Functionalized ABFs (f-ABFs) can be loaded with both hydrophilic and hydrophobic drugs, and controlled drug release triggered by temperature. ABFs have a great potential to be used in targeted and controlled drug delivery and for in vivo sensing. © 2013 IEEE.

关键词： Controlled drug delivery

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