A survey on active simultaneous localization and mapping: State of the art and new frontiers
Active simultaneous localization and mapping (SLAM) is the problem of planning and
controlling the motion of a robot to build the most accurate and complete model of the …
controlling the motion of a robot to build the most accurate and complete model of the …
Multi-UAV collaborative absolute vision positioning and navigation: a survey and discussion
P Tong, X Yang, Y Yang, W Liu, P Wu - Drones, 2023 - mdpi.com
The employment of unmanned aerial vehicles (UAVs) has greatly facilitated the lives of
humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the …
humans. Due to the mass manufacturing of consumer unmanned aerial vehicles and the …
Kimera: From SLAM to spatial perception with 3D dynamic scene graphs
A Rosinol, A Violette, M Abate… - … Journal of Robotics …, 2021 - journals.sagepub.com
Humans are able to form a complex mental model of the environment they move in. This
mental model captures geometric and semantic aspects of the scene, describes the …
mental model captures geometric and semantic aspects of the scene, describes the …
Kimera: an open-source library for real-time metric-semantic localization and mapping
We provide an open-source C++ library for real-time metric-semantic visual-inertial
Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual …
Simultaneous Localization And Mapping (SLAM). The library goes beyond existing visual …
Kimera-multi: Robust, distributed, dense metric-semantic slam for multi-robot systems
Multi-robot simultaneous localization and mapping (SLAM) is a crucial capability to obtain
timely situational awareness over large areas. Real-world applications demand multi-robot …
timely situational awareness over large areas. Real-world applications demand multi-robot …
Hierarchical representations and explicit memory: Learning effective navigation policies on 3d scene graphs using graph neural networks
Representations are crucial for a robot to learn effective navigation policies. Recent work
has shown that mid-level perceptual abstractions, such as depth estimates or 2D semantic …
has shown that mid-level perceptual abstractions, such as depth estimates or 2D semantic …
State‐of‐the‐art in automatic 3D reconstruction of structured indoor environments
Creating high‐level structured 3D models of real‐world indoor scenes from captured data is
a fundamental task which has important applications in many fields. Given the complexity …
a fundamental task which has important applications in many fields. Given the complexity …
3d-aware object goal navigation via simultaneous exploration and identification
Object goal navigation (ObjectNav) in unseen environments is a fundamental task for
Embodied AI. Agents in existing works learn ObjectNav policies based on 2D maps, scene …
Embodied AI. Agents in existing works learn ObjectNav policies based on 2D maps, scene …
Kimera-multi: a system for distributed multi-robot metric-semantic simultaneous localization and mapping
We present the first fully distributed multi-robot system for dense metric-semantic
Simultaneous Localization and Mapping (SLAM). Our system, dubbed Kimera-Multi, is …
Simultaneous Localization and Mapping (SLAM). Our system, dubbed Kimera-Multi, is …
View planning in robot active vision: A survey of systems, algorithms, and applications
Rapid development of artificial intelligence motivates researchers to expand the capabilities
of intelligent and autonomous robots. In many robotic applications, robots are required to …
of intelligent and autonomous robots. In many robotic applications, robots are required to …