4.2k citations · 4.7k across the 41 of their papers we have counts for
9 papers · 1 filter
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…
Mesh Manifold based Riemannian Motion Planning for Omnidirectional Micro Aerial Vehicles
Michael Pantic, Lionel Ott, Cesar Cadena +2
This paper presents a novel on-line path planning method that enables aerial robots to interact with surfaces. We present a solution to the problem of finding trajectories that dri…
PHASER: a Robust and Correspondence-free Global Pointcloud Registration
Lukas Bernreiter, Lionel Ott, Juan Nieto +2
We propose PHASER, a correspondence-free global registration of sensor-centric pointclouds that is robust to noise, sparsity, and partial overlaps. Our method can seamlessly handle…
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter
Michel Breyer, Jen Jen Chung, Lionel Ott +2
General robot grasping in clutter requires the ability to synthesize grasps that work for previously unseen objects and that are also robust to physical interactions, such as colli…
Active Model Learning using Informative Trajectories for Improved Closed-Loop Control on Real Robots
Weixuan Zhang, Marco Tognon, Lionel Ott +2
Model-based controllers on real robots require accurate knowledge of the system dynamics to perform optimally. For complex dynamics, first-principles modeling is not sufficiently p…