Search Results for author:
Found 34 papers, 21 papers with code
Spatial Computing and Intuitive Interaction: Bringing Mixed Reality and Robotics Together
Spatial computing -- the ability of devices to be aware of their surroundings and to represent this digitally -- offers novel capabilities in human-robot interaction.
Superquadric Object Representation for Optimization-based Semantic SLAM
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.
TSDF++: A Multi-Object Formulation for Dynamic Object Tracking and Reconstruction
The ability to simultaneously track and reconstruct multiple objects moving in the scene is of the utmost importance for robotic tasks such as autonomous navigation and interaction.
Hough2Map -- Iterative Event-based Hough Transform for High-Speed Railway Mapping
As a basis for a localization system we propose a complete on-board mapping pipeline able to map robust meaningful landmarks, such as poles from power lines, in the vicinity of the vehicle.
Active Model Learning using Informative Trajectories for Improved Closed-Loop Control on Real Robots
However, the efficient and effective data collection for such a data-driven system on real robots is still an open challenge.
Robotics Systems and Control Systems and Control
Volumetric Grasping Network: Real-time 6 DOF Grasp Detection in Clutter
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 collisions with other objects in the scene.
Robotics
NavRep: Unsupervised Representations for Reinforcement Learning of Robot Navigation in Dynamic Human Environments
In this work, we design ways in which unsupervised learning can be used to assist reinforcement learning for robot navigation.
Out-of-Distribution Detection for Automotive Perception
A mechanism to detect OOD samples is important for safety-critical applications, such as automotive perception, to trigger a safe fallback mode.
Freetures: Localization in Signed Distance Function Maps
Localization of a robotic system within a previously mapped environment is important for reducing estimation drift and for reusing previously built maps.
Robotics
IDOL: A Framework for IMU-DVS Odometry using Lines
The method's front-end extracts event clusters that belong to line segments in the environment whereas the back-end estimates the system's trajectory alongside the lines' 3D position by minimizing point-to-line distances between individual events and the lines' projection in the image space.
Robotics
Go Fetch: Mobile Manipulation in Unstructured Environments
With humankind facing new and increasingly large-scale challenges in the medical and domestic spheres, automation of the service sector carries a tremendous potential for improved efficiency, quality, and safety of operations.
Active Interaction Force Control for Contact-Based Inspection with a Fully Actuated Aerial Vehicle
A fully actuated and omnidirectional tilt-rotor aerial system is used to show capabilities of the control and planning methods.
Robotics
Whole-Body Control of a Mobile Manipulator using End-to-End Reinforcement Learning
Mobile manipulation is usually achieved by sequentially executing base and manipulator movements.
VersaVIS: An Open Versatile Multi-Camera Visual-Inertial Sensor Suite
Robust and accurate pose estimation is crucial for many applications in mobile robotics.
Robotics
SegMap: Segment-based mapping and localization using data-driven descriptors
We therefore present SegMap: a map representation solution for localization and mapping based on the extraction of segments in 3D point clouds.
An Efficient Sampling-based Method for Online Informative Path Planning in Unknown Environments
However, they are prone to local minima, resulting in sub-optimal trajectories, and sometimes do not reach global coverage.
Revisiting Boustrophedon Coverage Path Planning as a Generalized Traveling Salesman Problem
In this paper, we present a path planner for low-altitude terrain coverage in known environments with unmanned rotary-wing micro aerial vehicles (MAVs).
Robotics
The Fishyscapes Benchmark: Measuring Blind Spots in Semantic Segmentation
Deep learning has enabled impressive progress in the accuracy of semantic segmentation.
Ranked #13 on
Anomaly Detection
on Fishyscapes L&F
(using extra training data)
Volumetric Instance-Aware Semantic Mapping and 3D Object Discovery
To autonomously navigate and plan interactions in real-world environments, robots require the ability to robustly perceive and map complex, unstructured surrounding scenes.
Robotics
VIZARD: Reliable Visual Localization for Autonomous Vehicles in Urban Outdoor Environments
Changes in appearance is one of the main sources of failure in visual localization systems in outdoor environments.
Robotics
AgriColMap: Aerial-Ground Collaborative 3D Mapping for Precision Farming
The combination of aerial survey capabilities of Unmanned Aerial Vehicles with targeted intervention abilities of agricultural Unmanned Ground Vehicles can significantly improve the effectiveness of robotic systems applied to precision agriculture.
An informative path planning framework for UAV-based terrain monitoring
Unmanned Aerial Vehicles (UAVs) represent a new frontier in a wide range of monitoring and research applications.
Robotics
LandmarkBoost: Efficient Visual Context Classifiers for Robust Localization
We propose LandmarkBoost - an approach that, in contrast to the conventional 2D-3D matching methods, casts the search problem as a landmark classification task.
SegMap: 3D Segment Mapping using Data-Driven Descriptors
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.
Comparing Task Simplifications to Learn Closed-Loop Object Picking Using Deep Reinforcement Learning
We learn closed-loop policies mapping depth camera inputs to motion commands and compare different approaches to keep the problem tractable, including reward shaping, curriculum learning and using a policy pre-trained on a task with a reduced action set to warm-start the full problem.
Robotics
Sparse 3D Topological Graphs for Micro-Aerial Vehicle Planning
Micro-Aerial Vehicles (MAVs) have the advantage of moving freely in 3D space.
Robotics
C-blox: A Scalable and Consistent TSDF-based Dense Mapping Approach
Central to our approach is the representation of the environment as a collection of overlapping TSDF subvolumes.
Robotics
Safe Local Exploration for Replanning in Cluttered Unknown Environments for Micro-Aerial Vehicles
We perform extensive simulations to show that this system performs better than the standard approach of using an optimistic global planner, and also outperforms doing a single exploration step when the local planner is stuck.
Robotics
X-View: Graph-Based Semantic Multi-View Localization
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
This paper reports on a data-driven, interaction-aware motion prediction approach for pedestrians in environments cluttered with static obstacles.
Robotics
weedNet: Dense Semantic Weed Classification Using Multispectral Images and MAV for Smart Farming
In this paper, we present an approach for dense semantic weed classification with multispectral images collected by a micro aerial vehicle (MAV).
Voxblox: Incremental 3D Euclidean Signed Distance Fields for On-Board MAV Planning
We show that we can build TSDFs faster than Octomaps, and that it is more accurate to build ESDFs out of TSDFs than occupancy maps.
Robotics
SegMatch: Segment based loop-closure for 3D point clouds
We propose SegMatch, a reliable loop-closure detection algorithm based on the matching of 3D segments.
Robotics
Robust Visual Place Recognition With Graph Kernels
A novel method for visual place recognition is introduced and evaluated, demonstrating robustness to perceptual aliasing and observation noise.
