Search Results for author: Cesar Cadena

Found 39 papers, 23 papers with code

Fast Traversability Estimation for Wild Visual Navigation

no code implementations15 May 2023 Jonas Frey, Matias Mattamala, Nived Chebrolu, Cesar Cadena, Maurice Fallon, Marco Hutter

We demonstrate the advantages of our approach with experiments and ablation studies in challenging environments in forests, parks, and grasslands.

Navigate Self-Supervised Learning +1

3D VSG: Long-term Semantic Scene Change Prediction through 3D Variable Scene Graphs

1 code implementation16 Sep 2022 Samuel Looper, Javier Rodriguez-Puigvert, Roland Siegwart, Cesar Cadena, Lukas Schmid

In this work, we formalize the task of semantic scene variability estimation and identify three main varieties of semantic scene change: changes in the position of an object, its semantic state, or the composition of a scene as a whole.

Change Detection

SC-Explorer: Incremental 3D Scene Completion for Safe and Efficient Exploration Mapping and Planning

1 code implementation17 Aug 2022 Lukas Schmid, Mansoor Nasir Cheema, Victor Reijgwart, Roland Siegwart, Federico Tombari, Cesar Cadena

We further present an informative path planning method, leveraging the capabilities of our mapping approach and a novel scene-completion-aware information gain.

Efficient Exploration

SCIM: Simultaneous Clustering, Inference, and Mapping for Open-World Semantic Scene Understanding

1 code implementation21 Jun 2022 Hermann Blum, Marcus G. Müller, Abel Gawel, Roland Siegwart, Cesar Cadena

In order to operate in human environments, a robot's semantic perception has to overcome open-world challenges such as novel objects and domain gaps.

Object Discovery Scene Understanding +2

Sampling-free obstacle gradients and reactive planning in Neural Radiance Fields (NeRF)

no code implementations3 May 2022 Michael Pantic, Cesar Cadena, Roland Siegwart, Lionel Ott

This work investigates the use of Neural implicit representations, specifically Neural Radiance Fields (NeRF), for geometrical queries and motion planning.

Motion Planning

Descriptellation: Deep Learned Constellation Descriptors

no code implementations1 Mar 2022 Chunwei Xing, Xinyu Sun, Andrei Cramariuc, Samuel Gull, Jen Jen Chung, Cesar Cadena, Roland Siegwart, Florian Tschopp

However, handcrafted topological descriptors are hard to tune and not robust to environmental noise, drastic perspective changes, object occlusion or misdetections.

Simultaneous Localization and Mapping

NeuralBlox: Real-Time Neural Representation Fusion for Robust Volumetric Mapping

1 code implementation18 Oct 2021 Stefan Lionar, Lukas Schmid, Cesar Cadena, Roland Siegwart, Andrei Cramariuc

We present a novel 3D mapping method leveraging the recent progress in neural implicit representation for 3D reconstruction.

3D Reconstruction

See Yourself in Others: Attending Multiple Tasks for Own Failure Detection

1 code implementation6 Oct 2021 Boyang Sun, Jiaxu Xing, Hermann Blum, Roland Siegwart, Cesar Cadena

The proposed framework infers task failures by evaluating the individual prediction, across multiple visual perception tasks for different regions in an image.

Depth Estimation Semantic Segmentation

Superquadric Object Representation for Optimization-based Semantic SLAM

no code implementations20 Sep 2021 Florian Tschopp, Juan Nieto, Roland Siegwart, Cesar Cadena

Introducing semantically meaningful objects to visual Simultaneous Localization And Mapping (SLAM) has the potential to improve both the accuracy and reliability of pose estimates, especially in challenging scenarios with significant view-point and appearance changes.

Object Recognition Semantic SLAM

Self-Improving Semantic Perception for Indoor Localisation

1 code implementation4 May 2021 Hermann Blum, Francesco Milano, René Zurbrügg, Roland Siegward, Cesar Cadena, Abel Gawel

We find memory replay an effective measure to reduce forgetting and show how the robotic system can improve even when switching between different environments.

2D Semantic Segmentation Continual Learning

Pixel-wise Anomaly Detection in Complex Driving Scenes

1 code implementation CVPR 2021 Giancarlo Di Biase, Hermann Blum, Roland Siegwart, Cesar Cadena

The inability of state-of-the-art semantic segmentation methods to detect anomaly instances hinders them from being deployed in safety-critical and complex applications, such as autonomous driving.

Ranked #2 on Anomaly Detection on Lost and Found (using extra training data)

Anomaly Detection Autonomous Driving +1

The Hidden Uncertainty in a Neural Networks Activations

no code implementations5 Dec 2020 Janis Postels, Hermann Blum, Yannick Strümpler, Cesar Cadena, Roland Siegwart, Luc van Gool, Federico Tombari

We find that this leads to improved OOD detection of epistemic uncertainty at the cost of ambiguous calibration close to the data distribution.

Density Estimation Out of Distribution (OOD) Detection

Learning Trajectories for Visual-Inertial System Calibration via Model-based Heuristic Deep Reinforcement Learning

1 code implementation4 Nov 2020 Le Chen, Yunke Ao, Florian Tschopp, Andrei Cramariuc, Michel Breyer, Jen Jen Chung, Roland Siegwart, Cesar Cadena

Visual-inertial systems rely on precise calibrations of both camera intrinsics and inter-sensor extrinsics, which typically require manually performing complex motions in front of a calibration target.

reinforcement-learning Reinforcement Learning (RL)

Out-of-Distribution Detection for Automotive Perception

no code implementations3 Nov 2020 Julia Nitsch, Masha Itkina, Ransalu Senanayake, Juan Nieto, Max Schmidt, Roland Siegwart, Mykel J. Kochenderfer, Cesar Cadena

A mechanism to detect OOD samples is important for safety-critical applications, such as automotive perception, to trigger a safe fallback mode.

Autonomous Driving Object Recognition +1

Freetures: Localization in Signed Distance Function Maps

no code implementations19 Oct 2020 Alexander Millane, Helen Oleynikova, Christian Lanegger, Jeff Delmerico, Juan Nieto, Roland Siegwart, Marc Pollefeys, Cesar Cadena

Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps.


Empty Cities: a Dynamic-Object-Invariant Space for Visual SLAM

1 code implementation15 Oct 2020 Berta Bescos, Cesar Cadena, Jose Neira

The first challenge is addressed by the use of a convolutional network that learns a multi-class semantic segmentation of the image.

Semantic Segmentation Steganalysis +1

Deep Learning-based Human Detection for UAVs with Optical and Infrared Cameras: System and Experiments

no code implementations10 Aug 2020 Timo Hinzmann, Tobias Stegemann, Cesar Cadena, Roland Siegwart

In this paper, we present our deep learning-based human detection system that uses optical (RGB) and long-wave infrared (LWIR) cameras to detect, track, localize, and re-identify humans from UAVs flying at high altitude.

Human Detection

Learning Camera Miscalibration Detection

1 code implementation24 May 2020 Andrei Cramariuc, Aleksandar Petrov, Rohit Suri, Mayank Mittal, Roland Siegwart, Cesar Cadena

Self-diagnosis and self-repair are some of the key challenges in deploying robotic platforms for long-term real-world applications.

3D Gated Recurrent Fusion for Semantic Scene Completion

no code implementations17 Feb 2020 Yu Liu, Jie Li, Qingsen Yan, Xia Yuan, Chunxia Zhao, Ian Reid, Cesar Cadena

This paper tackles the problem of data fusion in the semantic scene completion (SSC) task, which can simultaneously deal with semantic labeling and scene completion.

3D Semantic Scene Completion Scene Understanding

SegMap: Segment-based mapping and localization using data-driven descriptors

2 code implementations27 Sep 2019 Renaud Dubé, Andrei Cramariuc, Daniel Dugas, Hannes Sommer, Marcin Dymczyk, Juan Nieto, Roland Siegwart, Cesar Cadena

We therefore present SegMap: a map representation solution for localization and mapping based on the extraction of segments in 3D point clouds.

Autonomous Driving Retrieval

This is not what I imagined: Error Detection for Semantic Segmentation through Visual Dissimilarity

no code implementations2 Sep 2019 David Haldimann, Hermann Blum, Roland Siegwart, Cesar Cadena

There has been a remarkable progress in the accuracy of semantic segmentation due to the capabilities of deep learning.

Semantic Segmentation

Learning Densities in Feature Space for Reliable Segmentation of Indoor Scenes

no code implementations1 Aug 2019 Nicolas Marchal, Charlotte Moraldo, Roland Siegwart, Hermann Blum, Cesar Cadena, Abel Gawel

Foreground objects are therefore detected as areas in an image for which the descriptors are unlikely given the background distribution.

Scene Understanding Semantic Segmentation

3D Multi-Robot Patrolling with a Two-Level Coordination Strategy

1 code implementation23 Jun 2019 Luigi Freda, Mario Gianni, Fiora Pirri, Abel Gawel, Renaud Dube, Roland Siegwart, Cesar Cadena

This target selection relies on a shared idleness representation and a coordination mechanism preventing topological conflicts.

Vocal Bursts Valence Prediction

OREOS: Oriented Recognition of 3D Point Clouds in Outdoor Scenarios

no code implementations19 Mar 2019 Lukas Schaupp, Mathias Bürki, Renaud Dubé, Roland Siegwart, Cesar Cadena

We introduce a novel method for oriented place recognition with 3D LiDAR scans.


Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery

1 code implementation IEEE ROBOTICS AND AUTOMATION LETTERS 2019 Margarita Grinvald, Fadri Furrer, Tonci Novkovic, Jen Jen Chung, Cesar Cadena, Roland Siegwart, Juan Nieto

To autonomously navigate and plan interactions in real-world environments, robots require the ability to robustly perceive and map complex, unstructured surrounding scenes.


VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments

no code implementations12 Feb 2019 Mathias Bürki, Lukas Schaupp, Marcin Dymczyk, Renaud Dubé, Cesar Cadena, Roland Siegwart, Juan Nieto

Changes in appearance is one of the main sources of failure in visual localization systems in outdoor environments.


From Coarse to Fine: Robust Hierarchical Localization at Large Scale

3 code implementations CVPR 2019 Paul-Edouard Sarlin, Cesar Cadena, Roland Siegwart, Marcin Dymczyk

In this paper we propose HF-Net, a hierarchical localization approach based on a monolithic CNN that simultaneously predicts local features and global descriptors for accurate 6-DoF localization.

Autonomous Driving Retrieval +2

Empty Cities: Image Inpainting for a Dynamic-Object-Invariant Space

1 code implementation20 Sep 2018 Berta Bescos, José Neira, Roland Siegwart, Cesar Cadena

In this paper we present an end-to-end deep learning framework to turn images that show dynamic content, such as vehicles or pedestrians, into realistic static frames.

Image Inpainting Semantic Segmentation +1

Modular Sensor Fusion for Semantic Segmentation

1 code implementation30 Jul 2018 Hermann Blum, Abel Gawel, Roland Siegwart, Cesar Cadena

Sensor fusion is a fundamental process in robotic systems as it extends the perceptual range and increases robustness in real-world operations.

Semantic Segmentation

SegMap: 3D Segment Mapping using Data-Driven Descriptors

1 code implementation25 Apr 2018 Renaud Dubé, Andrei Cramariuc, Daniel Dugas, Juan Nieto, Roland Siegwart, Cesar Cadena

While current methods extract descriptors for the single task of localization, SegMap leverages a data-driven descriptor in order to extract meaningful features that can also be used for reconstructing a dense 3D map of the environment and for extracting semantic information.

Data Compression

X-View: Graph-Based Semantic Multi-View Localization

no code implementations28 Sep 2017 Abel Gawel, Carlo Del Don, Roland Siegwart, Juan Nieto, Cesar Cadena

Our findings show that X-View is able to globally localize aerial-to-ground, and ground-to-ground robot data of drastically different view-points.

A Data-driven Model for Interaction-aware Pedestrian Motion Prediction in Object Cluttered Environments

no code implementations25 Sep 2017 Mark Pfeiffer, Giuseppe Paolo, Hannes Sommer, Juan Nieto, Roland Siegwart, Cesar Cadena

This paper reports on a data-driven, interaction-aware motion prediction approach for pedestrians in environments cluttered with static obstacles.


SegMatch: Segment based loop-closure for 3D point clouds

2 code implementations25 Sep 2016 Renaud Dubé, Daniel Dugas, Elena Stumm, Juan Nieto, Roland Siegwart, Cesar Cadena

We propose SegMatch, a reliable loop-closure detection algorithm based on the matching of 3D segments.


Past, Present, and Future of Simultaneous Localization And Mapping: Towards the Robust-Perception Age

2 code implementations19 Jun 2016 Cesar Cadena, Luca Carlone, Henry Carrillo, Yasir Latif, Davide Scaramuzza, Jose Neira, Ian Reid, John J. Leonard

Simultaneous Localization and Mapping (SLAM)consists in the concurrent construction of a model of the environment (the map), and the estimation of the state of the robot moving within it.


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