13 accepted papers
Belief Propagation (BP) is a powerful algorithm for distributed inference in probabilistic graphical models, however it quickly becomes infeasible for practical compute and memory budgets. Many efficient, non-parametric forms of BP have been developed, but the most popular is Gaussian Belief Propaga…
Multi-view 3D geometry networks offer a powerful prior but are prohibitively slow for real-time applications. We propose a novel way to adapt them for online use, enabling real-time 6-DoF pose tracking and online reconstruction of objects and scenes from monocular RGB videos. Our method rapidly sele
"CTSLAM has become a promising approach for fusing asynchronous and multi-modal sensor suites. Unlike discrete-time SLAM, which estimates poses discretely, CTSLAM uses continuous-time motion parametrizations, facilitating the integration of a variety of sensors such as rolling-shutter cameras, event…
We present a novel scalable, fully distributed, and online method for simultaneous localisation and extrinsic calibration for multi-robot setups. Individual a priori unknown robot poses are probabilistically inferred as robots sense each other while simultaneously calibrating their sensors and marke
We introduce Dream2Real, a robotics framework which integrates vision-language models (VLMs) trained on 2D data into a 3D object rearrangement pipeline. This is achieved by the robot autonomously constructing a 3D representation of the scene, where objects can be rearranged virtually and an image of…
Accurate 3D object pose estimation is key to enabling many robotic applications that involve challenging object interactions. In this work, we show that the density field created by a state-of-the-art efficient radiance field reconstruction method is suitable for highly accurate and robust pose esti…
This work addresses the issue of motion compensation and pattern tracking in event camera data. An event camera generates asynchronous streams of events triggered independently by each of the pixels upon changes in the observed intensity. Providing great advantages in low-light and rapid-motion scen…
State-of-the-art decentralized collaborative Simultaneous Localization And Mapping (SLAM) systems crucially lack the ability to effectively use well-mapped areas generated by other agents in the team for relocalization. This often leads to map redundancy between agents, inefficient communication, an…
With its considerable potential to address asynchronous multi-modal sensor fusion, the emerging paradigm of Continuous-Time (CT) Simultaneous Localization And Mapping (SLAM) has recently become a competitive alternative to conventional discrete-time approaches. Many fundamental research problems, su
In this paper, we introduce IDOL, an optimization-based framework for IMU-DVS Odometry using Lines. Event cameras, also called Dynamic Vision Sensors (DVSs), generate highly asynchronous streams of events triggered upon illumination changes for each individual pixel. This novel paradigm presents adv…
The recent emergence of bioinspired event cameras has opened up exciting new possibilities in high-frequency tracking, bringing robustness to common problems in traditional vision, such as lighting changes and motion blur. In order to leverage these attractive attributes of the event cameras, resear
Small Unmanned Aerial Vehicles (UAVs) are some of the most promising robotic platforms in a variety of applications due to their high mobility. Their restricted computational and payload capabilities, however, translate into significant challenges in automating their navigation. With Simultaneous Lo…
We propose in this work a new model of how the hidden human knowledge (HHK) of UAV pilots can be incorporated in the UAVs path planning generation. We intuitively know that human's pilots barely manage or even attempt to drive the UAV through a path that is optimal attending to some criteria as an o…