Concept
Détection de collision
Publications associées (84)
Social-Transmotion: Promptable Human Trajectory Prediction
Alexandre Massoud Alahi, Yang Gao, Kaouther Messaoud Ben Amor, Saeed Saadatnejad
Accurate human trajectory prediction is crucial for applications such as autonomous vehicles, robotics, and surveillance systems. Yet, existing models often fail to fully leverage the non-verbal social cues human subconsciously communicate when navigating ...
2024Rigidity-Aware Detection for 6D Object Pose Estimation
Mathieu Salzmann, Yinlin Hu, Jingyu Li, Rui Song
Most recent 6D object pose estimation methods first use object detection to obtain 2D bounding boxes before actually regressing the pose. However, the general object detection methods they use are ill-suited to handle cluttered scenes, thus producing poor ...
Los Alamitos2023Learning Transformations To Reduce the Geometric Shift in Object Detection
Mathieu Salzmann, Martin Pierre Engilberge, Vidit Vidit
The performance of modern object detectors drops when the test distribution differs from the training one. Most of the methods that address this focus on object appearance changes caused by, e.g., different illumination conditions, or gaps between syntheti ...
Los Alamitos2023Implicit Distance Functions: Learning and Applications in Robotics
In this thesis, we address the complex issue of collision avoidance in the joint space of robots. Avoiding collisions with both the robot's own body parts and obstacles in the environment is a critical constraint in motion planning and is crucial for ensur ...
EPFL2023AN UNSUPERVISED METHOD FOR THE DETECTION OF AND TRACKING OF TARGETS IN SPOTLIGHT MODE SAR IMAGES
Taking advantage of Capella's ability to dwell on a target for an extended period of time (nominally 30s) in its spotlight (SP) mode, an unsupervised methodology for detecting moving targets in this data is presented in this paper. By colourizing short seg ...
New York2023Automated post-earthquake damage assessment of stone masonry buildings integrating machine learning, computer vision, and physics-based modeling
Current post-earthquake damage assessment methodologies are not only time-consuming but also subjective in nature and difficult to document. Recent advancements in artificial intelligence and technological devices make it possible to accomplish this task a ...
EPFL2023Radatron: Accurate Detection Using Multi-resolution Cascaded MIMO Radar
Haitham Al Hassanieh, Junfeng Guan, Seyedsohrab Madani, Saurabh Gupta, Waleed Ahmed
Millimeter wave (mmWave) radars are becoming a more popular sensing modality in self-driving cars due to their favorable characteristics in adverse weather. Yet, they currently lack sufficient spatial resolution for semantic scene understanding. In this pa ...
SPRINGER INTERNATIONAL PUBLISHING AG2022Pedestrian 3D Bounding Box Prediction
Alexandre Massoud Alahi, Saeed Saadatnejad, Yi Zhou Ju
Safety is still the main issue of autonomous driving, and in order to be globally deployed, they need to predict pedestrians' motions sufficiently in advance. While there is a lot of research on coarse-grained (human center prediction) and fine-grained pre ...
2022Blind as a Bat: Audible Echolocation on Small Robots
Martin Vetterli, Mihailo Kolundzija, Adrien Guillaume Olivier Hoffet, Adam James Scholefield, Frederike Dümbgen
For safe and efficient operation, mobile robots need to perceive their environment, and in particular, perform tasks such as obstacle detection, localization, and mapping. Although robots are often equipped with microphones and speakers, the audio modality ...
2022Reactive Navigation in Crowds for Non-holonomic Robots with Convex Bounding Shape
Aude Billard, Diego Felipe Paez Granados, David Julian Gonon
This paper describes a novel method for non-holonomic robots of convex shape to avoid imminent collisions with moving obstacles. The method's purpose is to assist navigation in crowds by correcting steering from the robot's path planner or driver. We evalu ...
2021