Category Robotics Classification

Researchers from The University of Tokyo Institute of Industrial Science find that drones may be the next generation of communication bases to monitor the ocean and seafloor because of their high-speed positioning, stability, and efficiency.

A recent report from Meticulous Research found that the food robotics industry is anticipated to grow to an astounding $2 billion by 2028. This growth indicates a turning point in the food industry, driven by a number of rising global concerns and trends.

Baseball fans know the bitter heartbreak of calls that don't go their way—especially, a ball that should've been a strike. And, with advances in technology including computer vision, artificial intelligence, and the ubiquity of Wi-Fi, it would be easier than ever for baseball officials to replace humans with robotic umpires.

The number of collaborative mobile robots introduced in real-world settings is gradually increasing, with approximately 20,000 new installations per year. For their use to increase further, however, roboticists should ensure that these robots are both efficient and safe to use around humans.

Giving autonomous vehicles the 'green light' to break road rules is tackled in a new research in Ethics and Information Technology.

“S.A.M.” will be used as a communication intermediary, connecting a superintendent with a subcontractor from across a job site through two-way communications. It will also be able to traverse the site to remotely inspect work and capture progress photography and video.

If you don't get seasick, an autonomous boat might be the right mode of transportation for you.

A research team from the Interactive and Robotic Systems Laboratory at the Universitat Jaume I in Castelló has developed software that allows underwater robots with manipulation capabilities to be controlled remotely in a more efficient way, as it offers a computer graphic interface and prior realistic simulation. The new technology amends, in the context of underwater scenarios, the lack of simulation systems and realistic 3D interfaces that enable remote control of tasks in autonomous and teleoperated mobile manipulator robots.

Integral to, and supporting RoboFS is unique technology for automated receiving of incoming goods and their reconfiguration into SKU-specific containers and trays for subsequent high-bay storage and picking.

The IEEE International Conference on Automation Science and Engineering (CASE) is the flagship automation conference of the IEEE Robotics and Automation Society and constitutes the primary forum for cross-industry and multidisciplinary research in automation. Its goal is to provide a broad coverage and dissemination of foundational research in automation among researchers, academics, and practitioners. Here we bring you the online presentations by the finalists of the four awards given at the conference. Congratulations to all the finalists and winners!

Best student paper award

Winner

• Designing a User-Centred and Data-Driven Controller for Pushrim-Activated Power-Assisted Wheels: A Case Study
  Mahsa Khalili, H.F. Machiel Van der Loos and Jaimie Borisoff

Finalists

• Including Sparse Production Knowledge into Variational Autoencoders to Increase Anomaly Detection Reliability
  Tom Hammerbacher, Markus Lange-Hegermann, Gorden Platz

• Synthesis and Implementation of Distributed Supervisory Controllers with Communication Delays
  Lars Moormann, Reinier Hendrik Jacob Schouten, Joanna Maria Van de Mortel-Fronczak, Wan Fokkink, Jacobus E. Rooda

• Optimal Planning of Internet Data Centers Decarbonized by Hydrogen-Water-Based Energy Systems
  Jinhui Liu, Zhanbo Xu, Jiang Wu, kun liu, Xunhang Sun, Xiaohong Guan

• Deep Reinforcement Learning for Prefab Assembly Planning in Robot-Based Prefabricated Construction
  Zhu Aiyu, Gangyan Xu, Pieter Pauwels, Bauke de Vries, Meng Fang

• Singularity-Aware Motion Planning for Multi-Axis Additive Manufacturing
  Charlie C.L. Wang, Tianyu Zhang, Xiangjia Chen, Guoxin Fang, Yingjun Tian

Best conference paper award

Winner

• Extended Fabrication-Aware Convolution Learning Framework for Predicting 3D Shape Deformation in Additive Manufacturing
  Yuanxiang Wang, Cesar Ruiz, Qiang Huang

Finalists

• Probabilistic Movement Primitive Control Via Control Barrier Functions
  Mohammadreza Davoodi, Asif Iqbal, Joe Cloud, William Beksi, Nicholas Gans

• Efficient Optimization-Based Falsification of Cyber-Physical Systems with Multiple Conjunctive Requirements
  Logan Mathesen, Giulia Pedrielli, Georgios Fainekos

Best application paper award

Winner

• A Seamless Workflow for Design and Fabrication of Multimaterial Pneumatic Soft Actuators
  Lawrence Smith, Travis Hainsworth, Zachary Jordan, Xavier Bell, Robert MacCurdy

Finalists

• Dynamic Multi-Goal Motion Planning with Range Constraints for Autonomous Underwater Vehicles Following Surface Vehicles
  James McMahon, Erion Plaku

• OpenUAV Cloud Testbed: a Collaborative Design Studio for Field Robotics
  Harish Anand, Stephen A. Rees, Zhiang Chen, Ashwin Jose Poruthukaran, Sarah Bearman, Lakshmi Gana Prasad Antervedi, Jnaneshwar Das

Best healthcare automation paper award

Winner

• Hospital Beds Planning and Admission Control Policies for COVID-19 Pandemic: A Hybrid Computer Simulation Approach
  Yiruo Lu, Yongpei Guan, Xiang Zhong, Jennifer Fishe, Thanh Hogan

Finalists

• Rollout-Based Gantry Call-Back Control for Proton Therapy Systems
  Feifan Wang, Yu-Li Huang, Feng Ju

• Progress in Development of an Automated Mosquito Salivary Gland Extractor: A Step Forward to Malaria Vaccine Mass Production
  Wanze Li, Zhuoqun Zhang, Zhuohong He, Parth Vora, Alan Lai, Balazs Vagvolgyi, Simon Leonard, Anna Goodridge, Ioan Iulian Iordachita, Stephen L. Hoffman, Sumana Chakravarty, B Kim Lee Sim, Russell H. Taylor

Can intelligence be taught to robots? Advances in physical reservoir computing, a technology that makes sense of brain signals, could contribute to creating artificial intelligence machines that think like us.

Commercial unmanned aerial vehicles (UAVs) have the potential to almost halve the carbon dioxide (CO2) emissions of urban freight transport compared to small light commercial vehicles (LCVs), providing an unprecedented opportunity for the logistics industry to reduce its environmental impact. This is just one of the breakthrough findings from a brand new report published today by Inmarsat, the world leader in global, mobile satellite communications, and Cranfield University, examining the wealth of new possibilities and applications unlocked by commercial UAVs.

At the end of 2020, mobile robots were deployed in just over 9,000 separate customer sites. By 2025, deployments will have increased to over 53,000 sites. Whilst this may seem a lot, it is not even close to reaching the ceiling of market saturation.

Azobenzene-functionalized liquid crystalline materials can be operated by remote light-stimuli without complicated circuits or parts and thus are attracting great attention in fields such as human interfaces, haptic devices, and miniaturized soft robots.

Amit Goel, Director of Product Management for Autonomous Machines at NVIDIA, discusses the new collaboration between Open Robotics and NVIDIA. The collaboration will improve the way ROS and NVIDIA’s line of products such as Isaac SIM and the Jetson line of embedded boards operate together.

NVIDIA’s Isaac SIM lets developers build robust and scalable simulations. Dramatically reducing the costs of capturing real-world data and speeding up development time.

Their Jetson line of embedded boards is core to many robotics architectures, leveraging hardware-optimized chips for machine learning, computer vision, video processing, and more.

The improvements to ROS will allow robotics companies to better utilize the available computational power, while still developing on the robotics-centric platform familiar to many.

Amit Goel

Amit Goel is Director of Product Management for Autonomous Machines at NVIDIA, where he leads the product development of NVIDIA Jetson, the most advanced platform for AI computing at the edge.

Amit has more than 15 years of experience in the technology industry working in both software and hardware design roles. Prior to joining NVIDIA in 2011, he worked as a senior software engineer at Synopsys, where he developed algorithms for statistical performance modeling of digital designs.

Amit holds a Bachelor of Engineering in electronics and communication from Delhi College of Engineering, a Master of Science in electrical engineering from Arizona State University, and an MBA from the University of California at Berkeley.

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