Building general-purpose robots that operate seamlessly in any environment, with any object, and utilizing various skills to complete diverse tasks has been a long-standing goal in …
Transfer learning is a conceptually-enticing paradigm in pursuit of truly intelligent embodied agents. The core concept—reusing prior knowledge to learn in and from novel situations—is …
P Vestal, OK Kilag, GG Alvez, D Escabas… - … disciplinary Journal of …, 2023 - multijournals.org
This systematic literature review and meta-analysis illuminate the transformative potential of multisensory literacy instruction within the domain of literacy education. Drawing from a …
J Francis, N Kitamura, F Labelle, X Lu, I Navarro… - Journal of Artificial …, 2022 - jair.org
Recent advances in the areas of multimodal machine learning and artificial intelligence (AI) have led to the development of challenging tasks at the intersection of Computer Vision …
A holistic understanding of object properties across diverse sensory modalities (eg, visual, audio, and haptic) is essential for tasks ranging from object categorization to complex …
Robots frequently need to perceive object attributes, such as red, heavy, and empty, using multimodal exploratory behaviors, such as look, lift, and shake. One possible way for robots …
We need to look at our shoelaces as we first learn to tie them but having mastered this skill, can do it from touch alone. We call this phenomenon" sensory scaffolding": observation …
Humans learn about objects via interaction and using multiple perceptions, such as vision, sound, and touch. While vision can provide information about an object's appearance, non …
Autonomously exploring the unknown physical properties of novel objects such as stiffness, mass, center of mass, friction coefficient, and shape is crucial for autonomous robotic …