Accurate Pose Prediction on Signed Distance Fields for Mobile Ground Robots in Rough Terrain

Autonomous locomotion for mobile ground robots in unstructured environments such as waypoint navigation or flipper control requires a sufficiently accurate prediction of the robot-terrain interaction. Heuristics like occupancy grids or traversability maps are widely used but limit actions available to robots with active flippers as joint positions are not taken into account. We present a novel iterative geometric method to predict the 3D pose of mobile ground robots with active flippers on uneven ground with high accuracy and online planning capabilities. This is achieved by utilizing the ability of signed distance fields to represent surfaces with sub-voxel accuracy. The effectiveness of the presented approach is demonstrated on two different tracked robots in simulation and on a real platform. Compared to a tracking system as ground truth, our method predicts the robot position and orientation with an average accuracy of 3.11 cm and 3.91{\deg}, outperforming a recent heightmap-based approach. The implementation is made available as an open-source ROS package.Comment: Published in: 2023 IEEE International Symposium on Safety, Security, and Rescue Robotics (SSRR). Video: https://youtu.be/3kHDxPnEtH

Adaptive Observation Strategy for Dispersion Process Estimation Using Cooperating Mobile Sensors ⋆

Abstract: Efficient online state estimation of dynamic dispersion processes plays an important role in a variety of safety-critical applications. The use of mobile sensor platforms is increasingly considered in this context, but implies the generation of situation-dependent vehicle trajectories providing high information gain in real-time. In this paper, a new adaptive observation strategy is presented combining state estimation based on partial differential equation models of the dispersion process with a model-predictive control approach for multiple cooperating mobile sensors. In a repeating sequential procedure, based on the Ensemble Transform Kalman Filter, the uncertainty of the current estimate is determined and used to find valuable measurement locations. Those serve as target points for the controller providing optimal trajectories subject to the vehicles ’ motion dynamics and cooperation constraints. First promising results regarding accuracy and efficiency were obtained

Research in Nepal

Findings from University of Dayton geologist, Umesh Haritashya, after the deadly earthquake in Nepal April 25 will be published in a forthcoming article in Science, the leading journal on original scientific research

A Universal Footstep Planning Methodology for Continuous Walking in Challenging Terrain Applicable to Different Types of Legged Robots

In recent years, the capabilities of legged locomotion controllers have been significantly advanced enabling them to traverse basic types of uneven terrain without visual perception. However, safely and autonomously traversing longer distances over difficult uneven terrain requires appropriate motion planning using online collected environmental knowledge. In this paper, we present such a novel methodology for generic closed-loop preceding horizon footstep planning that enables legged robots equipped with capable locomotion controllers to autonomously traverse previously unknown terrain while continuously walking long distances. Hereby, our approach addresses the challenge of online terrain perception and soft real-time footstep planning. The proposed new formulation of the search-based planning problem makes no specific assumptions about the robot kinematics (e.g. number of legs) or the used locomotion control schemes. Therefore, it can be applied to a broad range of different types of legged robots. Unlike current methods, the proposed new framework can optionally consider the floating base as part of the state-space. It is possible to configure the complexity of the planner online, from efficiently solving tasks in flat terrain to using non-contiguous contacts in highly challenging terrain. Finally, the presented methodology is successfully applied and evaluated in virtual and real experiments on state of the art bipedal, quadrupedal, and a novel eight-legged robot

Структура и свойства керамического композиционного материала ZrO[2](MgO)-MgO с бимодальной пористостью

In this paper, different implementations of elastic joint models of industrial robots are described and compared established in ADAMS and SimMechanics. The models are intended to be used for path prediction under process force load due to Roboforming and High Speed Cutting, respectively. The computational results have been compared and showed good agreement. In experiments of robot forming and robot milling the measured and simulated path deviations according to the process force are compared. The experiments are descriped and the results are discussed within the paper as a basis of a next step model based compensation of the path deviation

RoboCup Soccer Leagues

RoboCup was created in 1996 by a group of Japanese, American, and European Artificial Intelligence and Robotics researchers with a formidable, visionary long-term challenge: “By 2050 a team of robot soccer players will beat the human World Cup champion team.” At that time, in the mid 90s, when there were very few effective mobile robots and the Honda P2 humanoid robot was presented to a stunning public for the first time also in 1996, the RoboCup challenge, set as an adversarial game between teams of autonomous robots, was fascinating and exciting. RoboCup enthusiastically and concretely introduced three robot soccer leagues, namely “Simulation,” “Small-Size,” and “Middle-Size,” as we explain below, and organized its first competitions at IJCAI’97 in Nagoya with a surprising number of 100 participants [RC97]. It was the beginning of what became a continously growing research community. RoboCup established itself as a structured organization (the RoboCup Federation www.RoboCup.org). RoboCup fosters annual competition events, where the scientific challenges faced by the researchers are addressed in a setting that is attractive also to the general public. and the RoboCup events are the ones most popular and attended in the research fields of AI and Robotics.RoboCup further includes a technical symposium with contributions relevant to the RoboCup competitions and beyond to the general AI and robotics

Design Concepts for a new Temporal Planning Paradigm

Abstract Throughout the history of space exploration, the complexity of missions has dramatically increased, from Sputnik in 1957 to MSL, a Mars rover mission launched in November 2011 with advanced autonomous capabilities. As a result, the mission plan that governs a spacecraft has also grown in complexity, pushing to the limit the capability of human operators to understand and manage it. However, the effective representation of large plans with multiple goals and constraints still represents a problem. In this paper, a novel approach to address this problem is presented. We propose a new planning paradigm named HTLN, intended to provide a compact and understandable representation of complex plans and goals based on Timeline planning and Hierarchical Temporal Networks. We also present the design of a planner based on HTLN, which enables new planning approaches that can improve the performance of present real-world domains

Emergency Response Person Localization and Vital Sign Estimation Using a Semi-Autonomous Robot Mounted SFCW Radar

The large number and scale of natural and man-made disasters have led to an urgent demand for technologies that enhance the safety and efficiency of search and rescue teams. Semi-autonomous rescue robots are beneficial, especially when searching inaccessible terrains, or dangerous environments, such as collapsed infrastructures. For search and rescue missions in degraded visual conditions or non-line of sight scenarios, radar-based approaches may contribute to acquire valuable, and otherwise unavailable information. This article presents a complete signal processing chain for radar-based multi-person detection, 2D-MUSIC localization and breathing frequency estimation. The proposed method shows promising results on a challenging emergency response dataset that we collected using a semi-autonomous robot equipped with a commercially available through-wall radar system. The dataset is composed of 62 scenarios of various difficulty levels with up to five persons captured in different postures, angles and ranges including wooden and stone obstacles that block the radar line of sight. Ground truth data for reference locations, respiration, electrocardiogram, and acceleration signals are included. The full emergency response benchmark data set as well as all codes to reproduce our results, are publicly available at https://doi.org/10.21227/4bzd-jm32.Comment: Dataset availabe at https://doi.org/10.21227/4bzd-jm32, code available at https://github.com/schrchr/radar-vitals-estimatio

Implications from Responsible Human-Robot Interaction with Anthropomorphic Service Robots for Design Science

Accelerated by the COVID-19 pandemic, anthropomorphic service robots are continuously penetrating various domains of our daily lives. With this development, the urge for an interdisciplinary approach to responsibly design human-robot interaction (HRI), with particular attention to human dignity, privacy, compliance, and transparency, increases. This paper contributes to design science, in developing a new artifact, i.e., an interdisciplinary framework for designing responsible HRI with anthropomorphic service robots, which covers the three design science research cycles. Furthermore, we propose a multi-method approach by applying this interdisciplinary framework. Thereby, our finding offer implications for designing HRI in a responsible manner