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3D3L: Deep Learned 3D Keypoint Detection and Description for LiDARs
(2021)2021 IEEE International Conference on Robotics and Automation (ICRA)With the advent of powerful, light-weight 3D LiDARs, they have become the hearth of many navigation and SLAM algorithms on various autonomous systems. Pointcloud registration methods working with unstructured pointclouds such as ICP are often computationally expensive or require a good initial guess. Furthermore, 3D feature-based registration methods have never quite reached the robustness of 2D methods in visual SLAM. With the continuously ...Conference Paper -
A Photorealistic Terrain Simulation Pipeline for Unstructured Outdoor Environments
(2021)2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Suitable datasets are an integral part of robotics research, especially for training neural networks in robot perception. However, in many domains, suitable real-world data are scarce and cannot be easily obtained. This problem is especially prevalent for unstructured outdoor environments, in particular, planetary ones. Recent advances in photorealistic simulations help researchers to simulate close-to-real data in many domains. Yet, there ...Conference Paper -
Modelling and Estimation of Human Walking Gait for Physical Human-Robot Interaction
(2021)2021 Aerial Robotic Systems Physically Interacting with the Environment (AIRPHARO)An approach to model and estimate human walking kinematics in real-time for Physical Human-Robot Interaction is presented. The human gait velocity along the forward and vertical direction of motion is modelled according to the Yoyo-model. We designed an Extended Kalman Filter (EKF) algorithm to estimate the frequency, bias and trigonometric state of a biased sinusoidal signal, from which the kinematic parameters of the Yoyo-model can be ...Conference Paper -
MultiPoint: Cross-spectral registration of thermal and optical aerial imagery
(2020)Proceedings of Machine Learning Research ~ Proceedings of the 2020 Conference on Robot LearningWhile optical cameras are ubiquitous in robotics, some robots can sense the world in several sections of the electromagnetic spectrum simultaneously, which can extend their capabilities in fundamental ways. For instance, many fixed-wing UAVs carry both optical and thermal imaging cameras, potentially allowing them to detect temperature difference-induced atmospheric updrafts, map their locations, and adjust their flight path accordingly ...Conference Paper -
IAN: Multi-behavior navigation planning for robots in real, crowded environments
(2020)2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)State-of-the-art approaches for robot navigation among humans are typically restricted to planar movement actions. This work addresses the question of whether it can be beneficial to use interaction actions, such as saying, touching, and gesturing, for the sake of allowing robots to navigate in unstructured, crowded environments. To do so, we first identify challenging scenarios to traditional motion planning methods. Based on the hypothesis ...Conference Paper -
Leveraging Stereo-Camera Data for Real-Time Dynamic Obstacle Detection and Tracking
(2020)2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Dynamic obstacle avoidance is one crucial component for compliant navigation in crowded environments. In this paper we present a system for accurate and reliable detection and tracking of dynamic objects using noisy point cloud data generated by stereo cameras. Our solution is real-time capable and specifically designed for the deployment on computationally-constrained unmanned ground vehicles. The proposed approach identifies individual ...Conference Paper -
Robot Navigation in Crowded Environments Using Deep Reinforcement Learning
(2020)2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)Mobile robots operating in public environments require the ability to navigate among humans and other obstacles in a socially compliant and safe manner. This work presents a combined imitation learning and deep reinforcement learning approach for motion planning in such crowded and cluttered environments. By separately processing information related to static and dynamic objects, we enable our network to learn motion patterns that are ...Conference Paper -
Dipper: A Dynamically Transitioning Aerial-Aquatic Unmanned Vehicle
(2021)Proceedings of Robotics: Science and Systems XVIIThe locomotion for many modern robotic systems is optimized for a single target domain - aerial, surface or underwater. In this work, we address the challenge of developing a robotic system capable of controlled motion in air and underwater. Further, we explore the particular challenge of dynamic transitions between air and water. We propose Dipper, an aerial-aquatic hybrid vehicle. Dipper is a lightweight fixed-wing unmanned aerial vehicle ...Conference Paper -
RoBoa: Construction and evaluation of a steerable vine robot for search and rescue applications
(2021)2021 IEEE 4th International Conference on Soft Robotics (RoboSoft)RoBoa is a vine-like search and rescue robot that can explore narrow and cluttered environments such as destroyed buildings. The robot assists rescue teams in finding and communicating with trapped people. It employs the principle of vine robots for locomotion, everting the tip of its tube to move forward. Inside the tube, pneumatic actuators enable lateral movement. The head carries sensors and is mounted outside at the tip of the tube. ...Conference Paper -
Linear vs nonlinear mpc for trajectory tracking applied to rotary wing micro aerial vehicles
(2017)IFAC-PapersOnLine ~ 20th IFAC World Congress. ProceedingsPrecise trajectory tracking is a crucial property for Micro Air Vehicles (MAVs) to operate in cluttered environment or under disturbances. In this paper we present a detailed comparison between two state-of-the-art model-based control techniques for MAV trajectory tracking. A classical Linear Model Predictive Controller (LMPC) is presented and compared against a more advanced Nonlinear Model Predictive Controller (NMPC) that considers the ...Conference Paper