4.2k citations · 4.7k across the 41 of their papers we have counts for
53 papers
Aerial Layouting: Design and Control of a Compliant and Actuated End-Effector for Precise In-flight Marking on Ceilings
Christian Lanegger, Marco Ruggia, Marco Tognon +2
Aerial robots have demonstrated impressive feats of precise control, such as dynamic flight through openings or highly complex choreographies. Despite the accuracy needed for these…
Self-Supervised Learning for Interactive Perception of Surgical Thread for Autonomous Suture Tail-Shortening
Vincent Schorp, Will Panitch, Kaushik Shivakumar +6
Accurate 3D sensing of suturing thread is a challenging problem in automated surgical suturing because of the high state-space complexity, thinness and deformability of the thread,…
Efficient volumetric mapping of multi-scale environments using wavelet-based compression
Victor Reijgwart, Cesar Cadena, Roland Siegwart +1
Volumetric maps are widely used in robotics due to their desirable properties in applications such as path planning, exploration, and manipulation. Constant advances in mapping tec…
Material-agnostic Shaping of Granular Materials with Optimal Transport
Nikhilesh Alatur, Olov Andersson, Roland Siegwart +1
From construction materials, such as sand or asphalt, to kitchen ingredients, like rice, sugar, or salt; the world is full of granular materials. Despite impressive progress in rob…
Neural Implicit Vision-Language Feature Fields
Kenneth Blomqvist, Francesco Milano, Jen Jen Chung +2
Recently, groundbreaking results have been presented on open-vocabulary semantic image segmentation. Such methods segment each pixel in an image into arbitrary categories provided…
Chasing Millimeters: Design, Navigation and State Estimation for Precise In-flight Marking on Ceilings
Christian Lanegger, Michael Pantic, Rik Bähnemann +2
Precise markings for drilling and assembly are crucial, laborious construction tasks. Aerial robots with suitable end-effectors are capable of markings at the millimeter scale. How…
Obstacle avoidance using raycasting and Riemannian Motion Policies at kHz rates for MAVs
Michael Pantic, Isar Meijer, Rik Bähnemann +5
In this paper, we present a novel method for using Riemannian Motion Policies on volumetric maps, shown in the example of obstacle avoidance for Micro Aerial Vehicles (MAVs). While…
A Framework for Collaborative Multi-Robot Mapping using Spectral Graph Wavelets
Lukas Bernreiter, Shehryar Khattak, Lionel Ott +3
The exploration of large-scale unknown environments can benefit from the deployment of multiple robots for collaborative mapping. Each robot explores a section of the environment a…
SphNet: A Spherical Network for Semantic Pointcloud Segmentation
Lukas Bernreiter, Lionel Ott, Roland Siegwart +1
Semantic segmentation for robotic systems can enable a wide range of applications, from self-driving cars and augmented reality systems to domestic robots. We argue that a spherica…
Baking in the Feature: Accelerating Volumetric Segmentation by Rendering Feature Maps
Kenneth Blomqvist, Lionel Ott, Jen Jen Chung +1
Methods have recently been proposed that densely segment 3D volumes into classes using only color images and expert supervision in the form of sparse semantically annotated pixels.…
Learning Agent-Aware Affordances for Closed-Loop Interaction with Articulated Objects
Giulio Schiavi, Paula Wulkop, Giuseppe Rizzi +3
Interactions with articulated objects are a challenging but important task for mobile robots. To tackle this challenge, we propose a novel closed-loop control pipeline, which integ…
Closed-Loop Next-Best-View Planning for Target-Driven Grasping
Michel Breyer, Lionel Ott, Roland Siegwart +1
Picking a specific object from clutter is an essential component of many manipulation tasks. Partial observations often require the robot to collect additional views of the scene b…
Team CERBERUS Wins the DARPA Subterranean Challenge: Technical Overview and Lessons Learned
Marco Tranzatto, Mihir Dharmadhikari, Lukas Bernreiter +33
This article presents the CERBERUS robotic system-of-systems, which won the DARPA Subterranean Challenge Final Event in 2021. The Subterranean Challenge was organized by DARPA with…
Learning Variable Impedance Control for Aerial Sliding on Uneven Heterogeneous Surfaces by Proprioceptive and Tactile Sensing
Weixuan Zhang, Lionel Ott, Marco Tognon +1
The recent development of novel aerial vehicles capable of physically interacting with the environment leads to new applications such as contact-based inspection. These tasks requi…
Robotic Maintenance of Road Infrastructures: The HERON Project
Iason Katsamenis, Matthaios Bimpas, Eftychios Protopapadakis +10
Of all public assets, road infrastructure tops the list. Roads are crucial for economic development and growth, providing access to education, health, and employment. The maintenan…
Sampling-free obstacle gradients and reactive planning in Neural Radiance Fields (NeRF)
Michael Pantic, Cesar Cadena, Roland Siegwart +1
This work investigates the use of Neural implicit representations, specifically Neural Radiance Fields (NeRF), for geometrical queries and motion planning. We show that by adding t…
Collaborative Robot Mapping using Spectral Graph Analysis
Lukas Bernreiter, Shehryar Khattak, Lionel Ott +3
In this paper, we deal with the problem of creating globally consistent pose graphs in a centralized multi-robot SLAM framework. For each robot to act autonomously, individual onbo…
Stein Particle Filter for Nonlinear, Non-Gaussian State Estimation
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
Estimation of a dynamical system's latent state subject to sensor noise and model inaccuracies remains a critical yet difficult problem in robotics. While Kalman filters provide th…
Semi-automatic 3D Object Keypoint Annotation and Detection for the Masses
Kenneth Blomqvist, Jen Jen Chung, Lionel Ott +1
Creating computer vision datasets requires careful planning and lots of time and effort. In robotics research, we often have to use standardized objects, such as the YCB object set…
Autonomous Teamed Exploration of Subterranean Environments using Legged and Aerial Robots
Mihir Kulkarni, Mihir Dharmadhikari, Marco Tranzatto +10
This paper presents a novel strategy for autonomous teamed exploration of subterranean environments using legged and aerial robots. Tailored to the fact that subterranean settings,…
Probabilistic Trajectory Prediction with Structural Constraints
Weiming Zhi, Lionel Ott, Fabio Ramos
This work addresses the problem of predicting the motion trajectories of dynamic objects in the environment. Recent advances in predicting motion patterns often rely on machine lea…
Learning ODEs via Diffeomorphisms for Fast and Robust Integration
Weiming Zhi, Tin Lai, Lionel Ott +2
Advances in differentiable numerical integrators have enabled the use of gradient descent techniques to learn ordinary differential equations (ODEs). In the context of machine lear…
Stein ICP for Uncertainty Estimation in Point Cloud Matching
Fahira Afzal Maken, Fabio Ramos, Lionel Ott
Quantification of uncertainty in point cloud matching is critical in many tasks such as pose estimation, sensor fusion, and grasping. Iterative closest point (ICP) is a commonly us…
Spherical Multi-Modal Place Recognition for Heterogeneous Sensor Systems
Lukas Bernreiter, Lionel Ott, Juan Nieto +2
In this paper, we propose a robust end-to-end multi-modal pipeline for place recognition where the sensor systems can differ from the map building to the query. Our approach operat…