Category robots in business

New algorithms will transform the foundations of computing

New algorithms will transform the foundations of computing

New algorithms will transform the foundations of computing

New algorithms will transform the foundations of computing

A simple sponge has improved how robots grasp, scientists from the University of Bristol have found.   

New algorithms will transform the foundations of computing

-Automate 2023 set record attendance with more than 30,000 registrants -Automate is heading to Chicago in 2024 and will return to Detroit in 2025

If the OEM uses well-designed, proven components, the mobile platform will provide many years of service, handling cumbersome, heavy loads efficiently with minimal downtime for maintenance.

A research collaboration between Cornell and the Max Planck Institute for Intelligent Systems has found an efficient way to expand the collective behavior of swarming microrobots: Mixing different sizes of the micron-scale 'bots enables them to self-organize into diverse patterns that can be manipulated when a magnetic field is applied. The technique even allows the swarm to "cage" passive objects and then expel them.

Our newsfeeds are filled with talk about the rapid rise of artificial intelligence (AI) in software such as ChatGPT and Stable Diffusion, which can quickly—albeit haphazardly—generate works such as essays and photographs from a text prompt. Reading these, you might be excused for thinking that writers and photographers are soon to go the way of the elevator operator, automated out of existence.

Learning from one's past mistakes is not limited to humans. Computers do it, too. In industries, this is done via computer-based control systems that help operate production systems. For industrial robots that perform specific tasks in batches, say producing clothing, computer chips, or baked goods, the most commonly used control technique is iterative learning control (ILC). Most industries still rely on ILC systems that use a learning strategy called the proportional-type update rule (PTUR). This technique improves the performance of ILC systems by repeating the same task over and over and updating its control input based on errors encountered in previous iterations.

Many existing robotics systems draw inspiration from nature, artificially reproducing biological processes, natural structures or animal behaviors to achieve specific goals. This is because animals and plants are innately equipped with abilities that help them to survive in their respective environments, and that could thus also improve the performance of robots outside of laboratory settings.

The Un-carrier helps Valmont capture mission-critical data in industry-first beyond visual line of sight (BVLOS) drone inspection operation

In this post we bring you all the paper awards finalists and winners presented during the 2023 edition of the IEEE International Conference on Robotics and Automation (ICRA). Congratulations to the winners and finalists!

ICRA 2023 Outstanding Paper

• Distributed Data-Driven Predictive Control for Multi-Agent Collaborative Legged Locomotion, by Fawcett, Randall; Amanzadeh, Leila; Kim, Jeeseop; Ames, Aaron; Akbari Hamed, Kaveh. (WINNER)
• Proficiency Self-Assessment without Breaking the Robot: Anomaly Detection using Assumption-Alignment Tracking from Safe Experiments, by Cao, Xuan; Crandall, Jacob W.; Pedersen, Ethan; Gautam, Alvika; Goodrich, Michael A.
• In-Hand Manipulation in Power Grasp: Design of an Adaptive Robot Hand with Active Surfaces, by Cai, Yilin; Yuan, Shenli.

ICRA 2023 Outstanding Automation Paper

• Towards Open-Set Material Recognition Using Robot Tactile Sensing, by Liu, Kun-Hong; Yang, Qianhui; Xie, Yu; Huang, Xiangyi.
• Target-Aware Implicit Mapping for Agricultural Crop Inspection, by Kelly, Shane; Riccardi, Alessandro; Marks, Elias Ariel; Magistri, Federico; Guadagnino, Tiziano; Chli, Margarita; Stachniss, Cyrill. (WINNER)
• Can Machines Garden? Systematically Comparing the AlphaGarden vs. Professional Horticulturalists, by Adebola, Simeon Oluwafunmilore; Parikh, Rishi; Presten, Mark; Sharma, Satvik; Aeron, Shrey; Rao, Ananth; Mukherjee, Sandeep; Qu, Tomson; Wistrom, Tina; Solowjow, Eugen; Goldberg, Ken.

ICRA 2023 Outstanding Student Paper

• M-EMBER: Tackling Long-Horizon Mobile Manipulation Via Factorized Domain Transfer, by Wu, Bohan; Martin-Martin, Roberto; Fei-Fei, Li.
• Robust Locomotion on Legged Robots through Planning on Motion Primitive Graphs, by Ubellacker, Wyatt; Ames, Aaron. (WINNER)
• Occlusion Reasoning for Skeleton Extraction of Self-Occluded Tree Canopies, by Kim, Chung Hee; Kantor, George.

ICRA 2023 Outstanding Deployed Systems Paper

• GUTS: Generalized Uncertainty-Aware Thompson Sampling for Multi-Agent Active Search, by Bakshi, Nikhil Angad; Gupta, Tejus; Ghods, Ramina; Schneider, Jeff. (WINNER)
• FRIDA: A Collaborative Robot Painter with a Differentiable, Real2Sim2Real Planning Environment, by Schaldenbrand, Peter; McCann, James; Oh, Jean.

ICRA 2023 Outstanding Dynamics and Control Paper

• Nonlinear Model Predictive Control of a 3D Hopping Robot: Leveraging Lie Group Integrators for Dynamically Stable Behaviors, by Csomay-Shanklin, Noel; Dorobantu, Victor; Ames, Aaron. (WINNER)
• Robust, High-Rate Trajectory Tracking on Insect-Scale Soft-Actuated Aerial Robots with Deep-Learned Tube MPC, by Tagliabue, Andrea; Hsiao, Yi-Hsuan; Fasel, Urban; Kutz, J. Nathan; Brunton, Steven; Chen, YuFeng; How, Jonathan.
• Autonomous Drifting with 3 Minutes of Data Via Learned Tire Models, by Djeumou, Franck; Goh, Jon; Topcu, Ufuk; Balachandran, Avinash.

ICRA 2023 Outstanding Healthcare and Medical Robotics Paper

• MRI-Powered Magnetic Miniature Capsule Robot with HIFU-Controlled On-Demand Drug Delivery, by Tiryaki, Mehmet Efe; Doğangün, Fatih; Dayan, Cem Balda; Wrede, Paul; Sitti, Metin.
• Real-Time Constrained 6D Object-Pose Tracking of an In-Hand Suture Needle for Minimally Invasive Robotic Surgery, by Chiu, Zih-Yun; Richter, Florian; Yip, Michael C. (WINNER)
• Exploring Robot-Assisted Optical Coherence Elastography for Surgical Palpation, by Chang, Yeonhee; Ahronovich, Elan; Simaan, Nabil; Song, Cheol.

ICRA 2023 Outstanding Locomotion Paper

• RAMP: Reaction-Aware Motion Planning of Multi-Legged Robots for Locomotion in Microgravity, by Ribeiro, Warley Francisco Rocha; Uno, Kentaro; Imai, Masazumi; Murase, Koki; Yoshida, Kazuya.
• Robust Locomotion on Legged Robots through Planning on Motion Primitive Graphs, by Ubellacker, Wyatt; Ames, Aaron.
• Multi-Segmented, Adaptive Feet for Versatile Legged Locomotion in Natural Terrain, by Chatterjee, Abhishek; Mo, An; Kiss, Bernadett; Gönen, Emre Cemal; Badri-Spröwitz, Alexander. (WINNER)

ICRA 2023 Outstanding Manipulation Paper

• M-EMBER: Tackling Long-Horizon Mobile Manipulation Via Factorized Domain Transfer, by Wu, Bohan; Martin-Martin, Roberto; Fei-Fei, Li.
• DexGraspNet: A Large-Scale Robotic Dexterous Grasp Dataset for General Objects Based on Simulation, by Wang, Ruicheng; Zhang, Jialiang; Chen, Jiayi; Xu, Yinzhen; Li, Puhao; Liu, Tengyu; Wang, He.
• In-Hand Manipulation in Power Grasp: Design of an Adaptive Robot Hand with Active Surfaces, by Cai, Yilin; Yuan, Shenli. (WINNER)

ICRA 2023 Outstanding Mechanisms and Design Paper

• New Bracket Polynomials Associated with the General Gough-Stewart Parallel Robot Singularities, by Thomas, Federico.
• A Compact, Two-Part Torsion Spring Architecture, by Bons, Zachary P; Thomas, Gray; Mooney, Luke; Rouse, Elliott.
• Contact Force Control with Continuously Compliant Robotic Legs, by Bendfeld, Robin; Remy, C. David. (WINNER)

ICRA 2023 Outstanding Multi-Robot Systems Paper

• Graph Neural Networks for Multi-Robot Active Information Acquisition, by Tzes, Mariliza; Bousias, Nikolaos; Chatzipantazis, Evangelos; Pappas, George J. (WINNER)
• Distributed Data-Driven Predictive Control for Multi-Agent Collaborative Legged Locomotion, by Fawcett, Randall; Amanzadeh, Leila; Kim, Jeeseop; Ames, Aaron; Akbari Hamed, Kaveh.
• GoRela: Go Relative for Viewpoint-Invariant Motion Forecasting, by Cui, Alexander; Casas Romero, Sergio; Wong, Kelvin; Suo, Simon; Urtasun, Raquel.

ICRA 2023 Outstanding Navigation Paper

• IMODE: Real-Time Incremental Monocular Dense Mapping Using Neural Field, by Matsuki, Hidenobu; Sucar, Edgar; Laidlow, Tristan; Wada, Kentaro; Scona, Raluca; Davison, Andrew J.
• SmartRainNet: Uncertainty Estimation for Laser Measurement in Rain, by Zhang, Chen; Huang, Zefan; Tung, Beatrix; Ang Jr, Marcelo H; Rus, Daniela. (WINNER)
• Online Whole-Body Motion Planning for Quadrotor Using Multi-Resolution Search, by Ren, Yunfan; Liang, Siqi; Zhu, Fangcheng; Lu, Guozheng; Zhang, Fu.

ICRA 2023 Outstanding Physical Human-Robot Interaction Paper

• A Control Approach for Human-Robot Ergonomic Payload Lifting, by Rapetti, Lorenzo; Sartore, Carlotta; Elobaid, Mohamed; Tirupachuri, Yeshasvi; Draicchio, Francesco; Kawakami, Tomohiro; Yoshiike, Takahide; Pucci, Daniele.
• Learning from Physical Human Feedback: An Object-Centric One-Shot Adaptation Method, by Shek, Alvin; Su, Bo Ying; Chn Rui; Liu, Changliu. (WINNER)
• Interactive Object Segmentation in 3D Point Clouds, by Kontogianni, Theodora; Celikkan, Ekin; Tang, Siyu; Schindler, Konrad.

ICRA 2023 Outstanding Planning Paper

• Obstacle-Aware Topological Planning Over Polyhedral Representation for Quadrotors, by Gao, Junjie; He, Fenghua; Zhang, Wei; Yao, Yu.
• Learning-Based Initialization of Trajectory Optimization for Path-Following Problems of Redundant Manipulators, by Yoon, Minsung; Kang, Mincheul; Park, Daehyung; Yoon, Sung-eui. (WINNER)
• A Multi-Step Dynamics Modeling Framework for Autonomous Driving in Multiple Environments, by Gibson, Jason; Vlahov, Bogdan; Fan, David D; Spieler, Patrick; Pastor, Daniel; Agha-mohammadi, Ali-akbar; Theodorou, Evangelos.

ICRA 2023 Outstanding Robot Learning Paper

• Code As Policies: Language Model Programs for Embodied Control, by Liang, Jacky; Huang, Wenlong; Xia, Fei; Xu, Peng; Hausman, Karol; Ichter, Brian; Florence, Peter; Zeng, Andy. (WINNER)
• Grounding Language with Visual Affordances Over Unstructured Data, by Mees, Oier; Borja Diaz, Jessica; Burgard, Wolfram.
• NeRF2Real: Sim2real Transfer of Vision-Guided Bipedal Motion Skills Using Neural Radiance Fields, by Byravan, Arunkumar; Humplik, Jan; Hasenclever, Leonard; Brussee, Arthur; Nori, Francesco; Haarnoja, Tuomas; Moran, Ben; Bohez, Steven; Sadeghi, Fereshteh; Vujatovic, Bojan; Heess, Nicolas.

ICRA 2023 Outstanding Sensors and Perception Paper

• Towards Consistent Batch State Estimation Using a Time-Correlated Measurement Noise Model, by Yoon, David Juny; Barfoot, Timothy.
• GMCR: Graph-Based Maximum Consensus Estimation for Point Cloud Registration, by Gentner, Michael; Murali, Prajval Kumar; Kaboli, Mohsen.
• Occlusion Reasoning for Skeleton Extraction of Self-Occluded Tree Canopies, by Kim, Chung Hee; Kantor, George. (WINNER)

Researchers have trained a robotic 'chef' to watch and learn from cooking videos, and recreate the dish itself.