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- Korea Advanced Institute of Science and TechnologyKR2 papers
- American Association of Variable Star ObserversUS1 paper
- Astronomical Institute of the Slovak Academy of SciencesSK1 paper
- Australian Centre for Robotic VisionAU1 paper
- British Astronomical AssociationGB1 paper
- Cornell UniversityUS1 paper
- Defense Advanced Research Projects AgencyUS1 paper
- Harvard UniversityUS1 paper
- Kootenay Association for Science & TechnologyCA1 paper
- Lunar and Planetary InstituteUS1 paper
- Main Astronomical ObservatoryUA1 paper
- Moscow Institute of Thermal TechnologyRU1 paper
9 papers
LVI-Q: Robust LiDAR-Visual-Inertial-Kinematic Odometry for Quadruped Robots Using Tightly-Coupled and Efficient Alternating Optimization
Kevin Christiansen Marsim, Minho Oh, Byeongho Yu +4
Autonomous navigation for legged robots in complex and dynamic environments relies on robust simultaneous localization and mapping (SLAM) systems to accurately map surroundings and…
Morphological Cognition: Classifying MNIST Digits Through Morphological Computation Alone
Alican Mertan, Nick Cheney
With the rise of modern deep learning, neural networks have become an essential part of virtually every artificial intelligence system, making it difficult even to imagine differen…
Evolutionary Brain-Body Co-Optimization Consistently Fails to Select for Morphological Potential
Alican Mertan, Nick Cheney
Brain-body co-optimization remains a challenging problem. To understand and overcome its challenges, we exhaustively map a morphology-fitness landscape: we train controllers for ea…
Animal Interaction with Autonomous Mobility Systems: Designing for Multi-Species Coexistence
Tram Thi Minh Tran, Xinyan Yu, Marius Hoggenmueller +5
Autonomous mobility systems increasingly operate in environments shared with animals, from urban pets to wildlife. However, their design has largely focused on human interaction, w…
Networks of Binary Necklaces Induced by Elementary Cellular Automata Rules
Lapo Frati, Csenge Petak, Nick Cheney
Elementary cellular automata deterministically map a binary sequence to another using simple local rules. Visualizing the structure of this mapping is difficult because the number…
DreamWaQ++: Obstacle-Aware Quadrupedal Locomotion With Resilient Multi-Modal Reinforcement Learning
I Made Aswin Nahrendra, Byeongho Yu, Minho Oh +5
Quadrupedal robots hold promising potential for applications in navigating cluttered environments with resilience akin to their animal counterparts. However, their floating base co…