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SemSegMap – 3D Segment-based Semantic Localization
(2021)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Localization is an essential task for mobile autonomous robotic systems that want to use pre-existing maps or create new ones in the context of SLAM. Today, many robotic platforms are equipped with high-accuracy 3D LiDAR sensors, which allow a geometric mapping, and cameras able to provide semantic cues of the environment. Segment-based mapping and localization have been applied with great success to 3D point-cloud data, while semantic ...Conference Paper -
Informative Path Planning for Active Field Mapping under Localization Uncertainty
(2020)2020 IEEE International Conference on Robotics and Automation (ICRA)Information gathering algorithms play a key role in unlocking the potential of robots for efficient data collection in a wide range of applications. However, most existing strategies neglect the fundamental problem of the robot pose uncertainty, which is an implicit requirement for creating robust, high-quality maps. To address this issue, we introduce an informative planning framework for active mapping that explicitly accounts for the ...Conference Paper -
Differential Sweep Attitude Control for Swept Wing UAVs
(2020)2020 International Conference on Unmanned Aircraft Systems (ICUAS)A novel approach for attitude control of swept wing unmanned aerial vehicles (UAVs) is presented, involving the use of only differential wing sweep and rudder deflection. An analytic aerodynamic model of the aircraft based on simple sweep theory is derived in a first step. The prediction of a vortex lattice method is then compared to the initial model. Based on the body moment analysis of the two models, design constraints and a control ...Conference Paper -
Out-of-Distribution Detection for Automotive Perception
(2021)2021 IEEE International Intelligent Transportation Systems Conference (ITSC)Neural networks (NNs) are widely used for object classification in autonomous driving. However, NNs can fail on input data not well represented by the training dataset, known as out-of-distribution (OOD) data. A mechanism to detect OOD samples is important for safety-critical applications, such as automotive perception, to trigger a safe fallback mode. NNs often rely on softmax normalization for confidence estimation, which can lead to ...Conference Paper -
Voxplan: A 3D Global Planner using Signed Distance Function Submaps
(2021)2021 IEEE International Conference on Robotics and Automation (ICRA)The ability to safely navigate through complex and cluttered environments is required for a wide range of robotics applications. This paper introduces a framework to compute safe global paths in maps represented as collections of 3D Signed Distance Function (SDF) submaps. Such maps are able to maintain global consistency in spite of odometry drift. However, computationally efficient global path planning in this context remains a challenging ...Conference Paper -
Unified Data Collection for Visual-Inertial Calibration via Deep Reinforcement Learning
(2022)2022 International Conference on Robotics and Automation (ICRA)Visual-inertial sensors have a wide range of applications in robotics. However, good performance often requires different sophisticated motion routines to accurately calibrate camera intrinsics and inter-sensor extrinsics. This work presents a novel formulation to learn a motion policy to be executed on a robot arm for automatic data collection for calibrating intrinsics and extrinsics jointly. Our approach models the calibration process ...Conference Paper -
Reactive Motion Planning for Rope Manipulation and Collision Avoidance using Aerial Robots
(2022)2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)In this work we address the challenging problem of manipulating a flexible link, like a rope, with an aerial robot. Inspired by spraying tasks in construction and maintenance scenarios, we consider the case in which an autonomous end-effector (e.g., a spray nozzle moved by a robot or a human operator) is connected to a fixed point by a rope (e.g., a hose). To avoid collisions between the rope and the environment while the end-effector ...Conference Paper -
Sampling-free obstacle gradients and reactive planning in Neural Radiance Fields
(2022)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 the capacity to infer occupancy in a radius to a pre trained NeRF we are effectively learning an approximation to a Euclidean Signed Distance Field (ESDF). Even more, using backward differentiation of the network, we readily obtain the obstacle gradients that are ...Conference Paper -
Closed-Loop Next-Best-View Planning for Target-Driven Grasping
(2022)IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022)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 before attempting a grasp. This paper proposes a closed-loop next-best-view planner that drives exploration based on occluded object parts. By continuously predicting grasps from an up-to-date scene reconstruction, our policy can decide online to finalize a grasp ...Conference Paper -
Object Finding in Cluttered Scenes Using Interactive Perception
(2020)2020 IEEE International Conference on Robotics and Automation (ICRA)Object finding in clutter is a skill that requires perception of the environment and in many cases physical interaction. In robotics, interactive perception defines a set of algorithms that leverage actions to improve the perception of the environment, and vice versa use perception to guide the next action. Scene interactions are difficult to model, therefore, most of the current systems use predefined heuristics. This limits their ability ...Conference Paper