Zobrazeno 1 - 10
of 4 511
pro vyhledávání: '"A. Carlone"'
Autor:
Lim, Hyungtae, Kim, Daebeom, Shin, Gunhee, Shi, Jingnan, Vizzo, Ignacio, Myung, Hyun, Park, Jaesik, Carlone, Luca
While global point cloud registration systems have advanced significantly in all aspects, many studies have focused on specific components, such as feature extraction, graph-theoretic pruning, or pose solvers. In this paper, we take a holistic view o
Externí odkaz:
http://arxiv.org/abs/2409.15615
Deep learning plays a critical role in vision-based satellite pose estimation. However, the scarcity of real data from the space environment means that deep models need to be trained using synthetic data, which raises the Sim2Real domain gap problem.
Externí odkaz:
http://arxiv.org/abs/2409.06240
We investigate the existence and the properties of normalized ground states of a nonlinear Schr\"odinger equation on a quantum hybrid formed by two planes connected at a point. The nonlinearities are of power type and $L^2$-subcritical, while the mat
Externí odkaz:
http://arxiv.org/abs/2407.19810
Applications from manipulation to autonomous vehicles rely on robust and general object tracking to safely perform tasks in dynamic environments. We propose the first certifiably optimal category-level approach for simultaneous shape estimation and p
Externí odkaz:
http://arxiv.org/abs/2406.16837
Autor:
Hu, Siyi, Arroyo, Diego Martin, Debats, Stephanie, Manhardt, Fabian, Carlone, Luca, Tombari, Federico
Realistic conditional 3D scene synthesis significantly enhances and accelerates the creation of virtual environments, which can also provide extensive training data for computer vision and robotics research among other applications. Diffusion models
Externí odkaz:
http://arxiv.org/abs/2405.21066
Autor:
Zhang, Harry, Carlone, Luca
We introduce CHAMP, a novel method for learning sequence-to-sequence, multi-hypothesis 3D human poses from 2D keypoints by leveraging a conditional distribution with a diffusion model. To predict a single output 3D pose sequence, we generate and aggr
Externí odkaz:
http://arxiv.org/abs/2407.06141
Publikováno v:
IEEE Robotics and Automation Letters, vol. 9, no. 12, pp. 10978-10985, Dec. 2024
We present a novel approach for long-term human trajectory prediction in indoor human-centric environments, which is essential for long-horizon robot planning in these environments. State-of-the-art human trajectory prediction methods are limited by
Externí odkaz:
http://arxiv.org/abs/2405.00552
Autor:
Maggio, Dominic, Chang, Yun, Hughes, Nathan, Trang, Matthew, Griffith, Dan, Dougherty, Carlyn, Cristofalo, Eric, Schmid, Lukas, Carlone, Luca
Modern tools for class-agnostic image segmentation (e.g., SegmentAnything) and open-set semantic understanding (e.g., CLIP) provide unprecedented opportunities for robot perception and mapping. While traditional closed-set metric-semantic maps were r
Externí odkaz:
http://arxiv.org/abs/2404.13696
We discuss the problem of establishing the existence of the Ground States for the subcritical focusing Nonlinear Schr\"odinger energy on a domain made of a line and a plane intersecting at a point. The problem is physically motivated by the experimen
Externí odkaz:
http://arxiv.org/abs/2404.07843
Recent work in the construction of 3D scene graphs has enabled mobile robots to build large-scale metric-semantic hierarchical representations of the world. These detailed models contain information that is useful for planning, however an open questi
Externí odkaz:
http://arxiv.org/abs/2403.08094