2021
April
Not All Errors Are Created Equal: Exploring Human Responses to Robot Errors with Varying Severity. By Stiber, M., & Huang, C. M. (2020, October). In Companion Publication of the 2020 International Conference on Multimodal Interaction (p. 97-101).
Since robots working in close proximity with people is becoming increasingly common, these researchers from Johns Hopkins University were interested in examining the reaction time and response type of people when unexpected robot behaviors occur. Are you working on the integration of collaborative robots into safety-sensitive applications? Read about their results in April’s paper of the month.
Read MoreMarch
Mobile Manipulator for Autonomous Localization, Grasping and Precise Placement of Construction Material in a Semi-structured Environment. By Petr Stibinger, George Broughton, Filip Majer, Zdenek Rozsypálek, Anthony Wang, Kshitij Jindal, Alex Zhou, Dinesh Thakur, Giuseppe Loianno, Tomás Krajník, and Martin Saska.
See how these researchers from NYU Tandon, University of Pennsylvania, and Czech Technical University overcame the challenges of operating UGV mounted manipulators in outdoors semi-structured environments with an autonomous mobile robot for construction applications in March’s paper of the month!
Read moreFebruary
A Motion Planning Algorithm for Redundant Manipulators Using Rapidly Exploring Randomized Trees and Artificial Potential Fields. By Anoush Sepehri and Amirreza Mirbeygi Moghaddam.
Just like robots, ideas are often better than the sum of their parts. See how these researchers from UBC and the University of Manitoba combined two well-known methods for obstacle avoidance with 7 DoF robots into a single generalized strategy that avoids the issue of both methods. The method is even showed to be transferable between different robot models!
Read moreJanuary
Optimal Grasping Pose Synthesis in a Constrained Environment. By Alessandro Altobelli, Ozan Tokatli, Guy Burroughes, and Robert Skilton, RACE, United Kingdom Atomic Energy Authority, Culham Science Centre.
Each different use case often imposes various limitations, making autonomous grasping almost always a significant challenge in the world of robotics. In this month's featured paper, see how researchers from the Culham Science Center managed to create an algorithm that solves the grasping problem for robots operating in constrained spaces like gloveboxes without needing time or resources to train an AI.
Read more2020
December
Robotics Utilization for Healthcare Digitization in Global COVID-19 Management. By Khan, Z. H., Siddique, A., & Lee, C. W. (2020), International Journal of Environmental Research and Public Health, 17(11), 3819.
Dive into the many different applications involving robots for healthcare and how the existing technology can be leveraged in order to contribute to the global effort in the fight against the COVID-19 pandemic. See the link below for this extensive but very accessible report from engineering and medical researchers in Pakistan.
Read moreNovember
Acoustic Collision Detection and Localization for Robot Manipulators. By Fan, X., Lee, D., Chen, Y., Prepscius, C., Isler, V., Jackel, L., ... & Lee, D. (2020). IROS.
A few months ago, we have shared a quick video presenting their work. Now that it was presented during 2020's IROS virtual event, you can read about how these researchers from Samsung AI Center - New York pulled-off near-perfect collision localization by using their new noise-proof sound-based algorithm in November's Paper of the Month!
Read moreOctober
Fast Object Pose Estimation Using Adaptive Threshold for Bin-Picking. By Wu Yan, Zhihao Xu, Xuefeng Zhou, Qianxing Su, Shuai Li, and Hongmin Wu.
Discover how researchers from the Guangdong Key Laboratory of Modern Control Technology were able to implement lightweight and ultra-fast object pose estimation ideal for large-scale production scenarios.
Read moreSeptember
Robot Learning and Execution of Collaborative Manipulation Plans from YouTube Cooking Videos. By Hejia Zhang and Stefanos Nikolaidis, Department of Computer Science, University of Southern California.
People often watch videos on the web to learn how to cook new recipes, assemble furniture, or repair a computer. We wish to enable robots with the very same capability. This is challenging; there is a large variation in manipulation actions and some videos even involve multiple persons, who collaborate by sharing and exchanging objects and tools.
Read more