Goto

Collaborating Authors

 shaft


Supplementary Material for Text Promptable Surgical Instrument Segmentation with Vision-Language Models Zijian Zhou

Neural Information Processing Systems

They are used in our experiments section. OpenAI GPT -4 based prompts The input template for OpenAI GPT -4 is defined as: Please describe the appearance of [class_name] in endoscopic surgery, and change the description to a phrase with subject, and not use colons. The dataset consists of both training and test cases. Each video is recorded at 25 FPS and has annotations for instruments and operation phases. For EndoVis2019, the results are shown in Tab. 1, our method (input size 448) notably surpasses the competition's top performers, with +3% increase in DSC and +2% enhancement in NSD, which demonstrates the superiority of our method.


Kinematically Controllable Cable Robots with Reconfigurable End-effectors

Zhang, Nan

arXiv.org Artificial Intelligence

To enlarge the translational workspace of cable-driven robots, one common approach is to increase the number of cables. However, this introduces two challenges: (1) cable interference significantly reduces the rotational workspace, and (2) the solution of tensions in cables becomes non-unique, resulting in difficulties for kinematic control of the robot. In this work, we design structurally simple reconfigurable end-effectors for cable robots. By incorporating a spring, a helical-grooved shaft, and a matching nut, relative linear motions between end-effector components are converted into relative rotations, thereby expanding the rotational workspace of the mechanism. Meanwhile, a bearing is introduced to provide an additional rotational degree of freedom, making the mechanism non-redundant. As a result, the robot's motion can be controlled purely through kinematics without additional tension sensing and control.


RAPID Hand Prototype: Design of an Affordable, Fully-Actuated Biomimetic Hand for Dexterous Teleoperation

Wan, Zhaoliang, Zhou, Zida, Bi, Zetong, Yang, Zehui, Ding, Hao, Cheng, Hui

arXiv.org Artificial Intelligence

This paper addresses the scarcity of affordable, fully-actuated five-fingered hands for dexterous teleoperation, which is crucial for collecting large-scale real-robot data within the "Learning from Demonstrations" paradigm. We introduce the prototype version of the RAPID Hand, the first low-cost, 20-degree-of-actuation (DoA) dexterous hand that integrates a novel anthropomorphic actuation and transmission scheme with an optimized motor layout and structural design to enhance dexterity. Specifically, the RAPID Hand features a universal phalangeal transmission scheme for the non-thumb fingers and an omnidirectional thumb actuation mechanism. Prioritizing affordability, the hand employs 3D-printed parts combined with custom gears for easier replacement and repair. We assess the RAPID Hand's performance through quantitative metrics and qualitative testing in a dexterous teleoperation system, which is evaluated on three challenging tasks: multi-finger retrieval, ladle handling, and human-like piano playing. The results indicate that the RAPID Hand's fully actuated 20-DoF design holds significant promise for dexterous teleoperation.


I discovered secret tunnels below Egypt's Giza pyramids... and they may lead to a forgotten underworld

Daily Mail - Science & tech

'Four dead and 12 injured' in Mississippi shooting after people descend on town for homecoming game Joe Biden, 82, receiving new treatment after'aggressive' cancer spread to his bones REVEALED: The secret George Soros network'behind America's street chaos'... and the dossier that shows how to stop it Tinnitus destroyed Peter's life but doctors dismissed him. Then he tried an extraordinary drug-free University of Cambridge-backed treatment that gives instant relief - no wonder medics say it's so'exciting' KENNEDY: Obama's bitter post about Trump's Gaza peace deal proves what I've long suspected about Barry... and it would make Sigmund Freud blush Gold is soaring... here's what the pros say you should do with your 401(k) before it's too late Model dubbed'the world's most beautiful girl' when she was six is now all grown up and looks VERY different as she poses up a storm at Paris Fashion Week Teacher was'so high on cocaine she thought one of her students was her dog' But now, a royal insider claims they're'just as entitled as their parents' with'shady friends' Heartbreaking moment NFL reporter makes brutal comment about player Xavier Legette's dead father in locker room interview Experts reveal the surprising TRUTH behind RFK Jr's link between circumcision and autism Bombshell records that damn Letitia James and show Trump was RIGHT... and the staggering sum she was swindling Trump starts DOGE 2.0 as mass layoffs take place across federal government amid shutdown Famed'Big Short' investor gives terrifying verdict on Trump hammering China with 100 PERCENT tariff... and issues doomsday warning to Wall Street Jennifer Aniston, you've betrayed every woman with your selfish admission about not having children: CAROLINE BULLOCK I discovered secret tunnels below Egypt's Giza pyramids... and they may lead to a forgotten underworld On the northeastern edge of the Giza Plateau, I discovered three perfectly cut shafts hidden beneath the sands. They sit in the triangle between the Great Sphinx, Khufu's Pyramid and Khafre's Pyramid, and may open into a long-forgotten underground world. These are not water wells. They bear no inscriptions, no signs of casual digging, and their geometry is too precise, their walls too smooth, their design too deliberate.


Supplementary Material for Text Promptable Surgical Instrument Segmentation with Vision-Language Models Zijian Zhou

Neural Information Processing Systems

They are used in our experiments section. OpenAI GPT -4 based prompts The input template for OpenAI GPT -4 is defined as: Please describe the appearance of [class_name] in endoscopic surgery, and change the description to a phrase with subject, and not use colons. The dataset consists of both training and test cases. Each video is recorded at 25 FPS and has annotations for instruments and operation phases. For EndoVis2019, the results are shown in Tab. 1, our method (input size 448) notably surpasses the competition's top performers, with +3% increase in DSC and +2% enhancement in NSD, which demonstrates the superiority of our method.


Transformer Vibration Forecasting for Advancing Rail Safety and Maintenance 4.0

Larese, Darío C., Cerrada, Almudena Bravo, Tomei, Gabriel Dambrosio, Guerrero-López, Alejandro, Olmos, Pablo M., García, María Jesús Gómez

arXiv.org Machine Learning

Maintaining railway axles is critical to preventing severe accidents and financial losses. The railway industry is increasingly interested in advanced condition monitoring techniques to enhance safety and efficiency, moving beyond traditional periodic inspections toward Maintenance 4.0. This study introduces a robust Deep Autoregressive solution that integrates seamlessly with existing systems to avert mechanical failures. Our approach simulates and predicts vibration signals under various conditions and fault scenarios, improving dataset robustness for more effective detection systems. These systems can alert maintenance needs, preventing accidents preemptively. We use experimental vibration signals from accelerometers on train axles. Our primary contributions include a transformer model, ShaftFormer, designed for processing time series data, and an alternative model incorporating spectral methods and enhanced observation models. Simulating vibration signals under diverse conditions mitigates the high cost of obtaining experimental signals for all scenarios. Given the non-stationary nature of railway vibration signals, influenced by speed and load changes, our models address these complexities, offering a powerful tool for predictive maintenance in the rail industry.


Electrostatic Clutches Enable High-Force Mechanical Multiplexing: Demonstrating Single-Motor Full-Actuation of a 4-DoF Hand

Amish, Timothy E., Auletta, Jeffrey T., Kessens, Chad C., Smith, Joshua R., Lipton, Jeffrey I.

arXiv.org Artificial Intelligence

This paper introduces a novel mechanical multiplexing system powered by electrostatic capstan clutches, enabling high-force, single-motor control of multiple degrees of freedom (DoF). The system is capable of both bidirectional single-input single-output time-division and single-input multiple-output multiplexing to actuate a commercial 4-DoF robotic hand with a single motor. Our mechanical multiplexer is also capable of powerless position holding owing to its use of a leadscrew nut acting as the output. Experimental results demonstrate the effectiveness of this approach, achieving individual and simultaneous actuation. This innovation offers a scalable solution for high-DoF robotic systems, providing a path to efficient actuation in robotic platforms.


Bridging Hard and Soft: Mechanical Metamaterials Enable Rigid Torque Transmission in Soft Robots

Carton, Molly, Kowalewski, Jakub F., Guo, Jiani, Alpert, Jacob F., Garg, Aman, Revier, Daniel, Lipton, Jeffrey Ian

arXiv.org Artificial Intelligence

Torque and continuous rotation are fundamental methods of actuation and manipulation in rigid robots. Soft robot arms use soft materials and structures to mimic the passive compliance of biological arms that bend and extend. This use of compliance prevents soft arms from continuously transmitting and exerting torques to interact with their environment. Here, we show how relying on patterning structures instead of inherent material properties allows soft robotic arms to remain compliant while continuously transmitting torque to their environment. We demonstrate a soft robotic arm made from a pair of mechanical metamaterials that act as compliant constant-velocity joints. The joints are up to 52 times stiffer in torsion than bending and can bend up to 45{\deg}. This robot arm can continuously transmit torque while deforming in all other directions. The arm's mechanical design achieves high motion repeatability (0.4 mm and 0.1{\deg}) when tracking trajectories. We then trained a neural network to learn the inverse kinematics, enabling us to program the arm to complete tasks that are challenging for existing soft robots such as installing light bulbs, fastening bolts, and turning valves. The arm's passive compliance makes it safe around humans and provides a source of mechanical intelligence, enabling it to adapt to misalignment when manipulating objects. This work will bridge the gap between hard and soft robotics with applications in human assistance, warehouse automation, and extreme environments.


Efficient Symmetry-Aware Materials Generation via Hierarchical Generative Flow Networks

Nguyen, Tri Minh, Tawfik, Sherif Abdulkader, Tran, Truyen, Gupta, Sunil, Rana, Santu, Venkatesh, Svetha

arXiv.org Artificial Intelligence

Discovering new solid-state materials requires rapidly exploring the vast space of crystal structures and locating stable regions. Generating stable materials with desired properties and compositions is extremely difficult as we search for very small isolated pockets in the exponentially many possibilities, considering elements from the periodic table and their 3D arrangements in crystal lattices. Materials discovery necessitates both optimized solution structures and diversity in the generated material structures. Existing methods struggle to explore large material spaces and generate diverse samples with desired properties and requirements. We propose the Symmetry-aware Hierarchical Architecture for Flow-based Traversal (SHAFT), a novel generative model employing a hierarchical exploration strategy to efficiently exploit the symmetry of the materials space to generate crystal structures given desired properties. In particular, our model decomposes the exponentially large materials space into a hierarchy of subspaces consisting of symmetric space groups, lattice parameters, and atoms. We demonstrate that SHAFT significantly outperforms state-of-the-art iterative generative methods, such as Generative Flow Networks (GFlowNets) and Crystal Diffusion Variational AutoEncoders (CDVAE), in crystal structure generation tasks, achieving higher validity, diversity, and stability of generated structures optimized for target properties and requirements.


A Preliminary Add-on Differential Drive System for MRI-Compatible Prostate Robotic System

Zhao, Zhanyue, Jiang, Yiwei, Bales, Charles, Wang, Yang, Fischer, Gregory

arXiv.org Artificial Intelligence

MRI-targeted biopsy has shown significant advantages over conventional random sextant biopsy, detecting more clinically significant cancers and improving risk stratification. However, needle targeting accuracy, especially in transperineal MRI-guided biopsies, presents a challenge due to needle deflection. This can negatively impact patient outcomes, leading to repeated sampling and inaccurate diagnoses if cancerous tissue isn't properly collected. To address this, we developed a novel differential drive prototype designed to improve needle control and targeting precision. This system, featuring a 2-degree-of-freedom (2-DOF) MRI-compatible cooperative needle driver, distances the robot from the MRI imaging area, minimizing image artifacts and distortions. By using two motors for simultaneous needle insertion and rotation without relative movement, the design reduces MRI interference. In this work, we introduced two mechanical differential drive designs: the ball screw/spline and lead screw/bushing types, and explored both hollow-type and side-pulley differentials. Validation through low-resolution rapid-prototyping demonstrated the feasibility of differential drives in prostate biopsies, with the custom hollow-type hybrid ultrasonic motor (USM) achieving a rotary speed of 75 rpm. The side-pulley differential further increased the speed to 168 rpm, ideal for needle rotation applications. Accuracy assessments showed minimal errors in both insertion and rotation motions, indicating that this proof-of-concept design holds great promise for further development. Ultimately, the differential drive offers a promising solution to the critical issue of needle targeting accuracy in MRI-guided prostate biopsies.