794 research outputs found
Teleoperation Methods for High-Risk, High-Latency Environments
In-Space Servicing, Assembly, and Manufacturing (ISAM) can enable larger-scale and longer-lived infrastructure projects in space, with interest ranging from commercial entities to the US government. Servicing, in particular, has the potential to vastly increase the usable lifetimes of satellites. However, the vast majority of spacecraft on low Earth orbit today were not designed to be serviced on-orbit. As such, several of the manipulations during servicing cannot easily be automated and instead require ground-based teleoperation.
Ground-based teleoperation of on-orbit robots brings its own challenges of high latency communications, with telemetry delays of several seconds, and difficulties in visualizing the remote environment due to limited camera views. We explore teleoperation methods to alleviate these difficulties, increase task success, and reduce operator load.
First, we investigate a model-based teleoperation interface intended to provide the benefits of direct teleoperation even in the presence of time delay. We evaluate the model-based teleoperation method using professional robot operators, then use feedback from that study to inform the design of a visual planning tool for this task, Interactive Planning and Supervised Execution (IPSE). We describe and evaluate the IPSE system and two interfaces, one 2D using a traditional mouse and keyboard and one 3D using an Intuitive Surgical da Vinci master console. We then describe and evaluate an alternative 3D interface using a Meta Quest head-mounted display. Finally, we describe an extension of IPSE to allow human-in-the-loop planning for a redundant robot. Overall, we find that IPSE improves task success rate and decreases operator workload compared to a conventional teleoperation interface
Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes
Robotic Information Gathering (RIG) is a foundational research topic that
answers how a robot (team) collects informative data to efficiently build an
accurate model of an unknown target function under robot embodiment
constraints. RIG has many applications, including but not limited to autonomous
exploration and mapping, 3D reconstruction or inspection, search and rescue,
and environmental monitoring. A RIG system relies on a probabilistic model's
prediction uncertainty to identify critical areas for informative data
collection. Gaussian Processes (GPs) with stationary kernels have been widely
adopted for spatial modeling. However, real-world spatial data is typically
non-stationary -- different locations do not have the same degree of
variability. As a result, the prediction uncertainty does not accurately reveal
prediction error, limiting the success of RIG algorithms. We propose a family
of non-stationary kernels named Attentive Kernel (AK), which is simple, robust,
and can extend any existing kernel to a non-stationary one. We evaluate the new
kernel in elevation mapping tasks, where AK provides better accuracy and
uncertainty quantification over the commonly used stationary kernels and the
leading non-stationary kernels. The improved uncertainty quantification guides
the downstream informative planner to collect more valuable data around the
high-error area, further increasing prediction accuracy. A field experiment
demonstrates that the proposed method can guide an Autonomous Surface Vehicle
(ASV) to prioritize data collection in locations with significant spatial
variations, enabling the model to characterize salient environmental features.Comment: International Journal of Robotics Research (IJRR). arXiv admin note:
text overlap with arXiv:2205.0642
Beam scanning by liquid-crystal biasing in a modified SIW structure
A fixed-frequency beam-scanning 1D antenna based on Liquid Crystals (LCs) is designed for application in 2D scanning with lateral alignment. The 2D array environment imposes full decoupling of adjacent 1D antennas, which often conflicts with the LC requirement of DC biasing: the proposed design accommodates both. The LC medium is placed inside a Substrate Integrated Waveguide (SIW) modified to work as a Groove Gap Waveguide, with radiating slots etched on the upper broad wall, that radiates as a Leaky-Wave Antenna (LWA). This allows effective application of the DC bias voltage needed for tuning the LCs. At the same time, the RF field remains laterally confined, enabling the possibility to lay several antennas in parallel and achieve 2D beam scanning. The design is validated by simulation employing the actual properties of a commercial LC medium
Accustomed to Obedience?
Many histories of Ancient Greece center their stories on Athens, but what would that history look like if they didn’t? There is another way to tell this story, one that situates Greek history in terms of the relationships between smaller Greek cities and in contact with the wider Mediterranean. In this book, author Joshua P. Nudell offers a new history of the period from the Persian wars to wars that followed the death of Alexander the Great, from the perspective of Ionia. While recent scholarship has increasingly treated Greece through the lenses of regional, polis, and local interaction, there has not yet been a dedicated study of Classical Ionia. This book fills this clear gap in the literature while offering Ionia as a prism through which to better understand Classical Greece.
This book offers a clear and accessible narrative of the period between the Persian Wars and the wars of the early Hellenistic period, two nominal liberations of the region. The volume complements existing histories of Classical Greece. Close inspection reveals that the Ionians were active partners in the imperial endeavor, even as imperial competition constrained local decision-making and exacerbated local and regional tensions. At the same time, the book offers interventions on critical issues related to Ionia such as the Athenian conquest of Samos, rhetoric about the freedom of the Greeks, the relationship between Ionian temple construction and economic activity, the status of the Panionion, Ionian poleis and their relationship with local communities beyond the circle of the dodecapolis, and the importance of historical memory to our understanding of ancient Greece. The result is a picture of an Aegean world that is more complex and less beholden narratives that give primacy to the imperial actors at the expense of local developments
Meta-Science:Towards a Science of Meaning and Complex Solutions
Science has lost its ethical imperatives as it moved away from a science of ought to a science of is. Subsequently, it might have answers for how we can address global challenges, such as climate change and poverty, but not why we should. This supposedly neutral stance leaves it to politics and religions (in the sense of non-scientific fields of social engagement) to fill in the values. The problem is that through this concession, science implicitly acknowledges that it is not of universal relevance.Objective knowledge, as Karl Popper calls for, might be less easily attainable in the world of ideas and within the confines of scientific idealism. However, if ideas, values and meaning have equal claim to be drivers of change in the sense of causation, aspiring to identify objective knowledge about the world of ideas and of meaning is necessary. If the sciences and disciplines aim to give objectively valid reasons for our actions (and for how to address global challenges), we need to elevate the study of meaning beyond the cultural, disciplinary and ideational delineations. We need to come to a meta understanding of values and meaning equal to objective knowledge about the material world. But differently than in the material world this meta understanding needs to incorporate individual and subjective experiences as cornerstones of objectivity on a meta-level.We need a science of meaning; one that can scientifically answer Kant’s third question of “what may we hope for”
Sampling-Based Exploration Strategies for Mobile Robot Autonomy
A novel, sampling-based exploration strategy is introduced for Unmanned Ground Vehicles (UGV) to efficiently map large GPS-deprived underground environments. It is compared to state-of-the-art approaches and performs on a similar level, while it is not designed for a specific robot or sensor configuration like the other approaches. The introduced exploration strategy, which is called Random-Sampling-Based Next-Best View Exploration (RNE), uses a Rapidly-exploring Random Graph (RRG) to find possible view points in an area around the robot. They are compared with a computation-efficient Sparse Ray Polling (SRP) in a voxel grid to find the next-best view for the exploration. Each node in the exploration graph built with RRG is evaluated regarding the ability of the UGV to traverse it, which is derived from an occupancy grid map. It is also used to create a topology-based graph where nodes are placed centrally to reduce the risk of collisions and increase the amount of observable space. Nodes that fall outside the local exploration area are stored in a global graph and are connected with a Traveling Salesman Problem solver to explore them later
Multi-scale Pedestrian Navigation and Movement in Urban Areas
Sustainable transport planning highlights the importance of walking to low-carbon
and healthy urban transport systems. Studies have identified multiple ways in which
vehicle traffic can negatively impact pedestrians and inhibit walking intentions.
However, pedestrian-vehicle interactions are underrepresented in models of pedestrian
mobility. This omission limits the ability of transport simulations to support
pedestrian-centric street design. Pedestrian navigation decisions take place simultaneously
at multiple spatial scales. Yet most models of pedestrian behaviour focus
either on local physical interactions or optimisation of routes across a road network.
This thesis presents a novel hierarchical pedestrian route choice framework that
integrates dynamic, perceptual decisions at the street level with abstract, network
based decisions at the neighbourhood level. The framework is based on Construal
Level Theory which states that decision makers construe decisions based on their
psychological distance from the object of the decision. The route choice framework
is implemented in a spatial agent-based simulation in which pedestrian and vehicle
agents complete trips in an urban environment. Global sensitivity analysis is used to
explore the behaviour produced by the multi-scale pedestrian route choice model.
Finally, simulation experiments are used to explore the impacts of restrictions to
pedestrian movement. The results demonstrate the potential insights that can be
gained by linking street scale movement and interactions with neighbourhood level
mobility patterns
Exploring Robot Teleoperation in Virtual Reality
This thesis presents research on VR-based robot teleoperation with a focus on remote environment visualisation in virtual reality, the effects of remote environment reconstruction scale in virtual reality on the human-operator's ability to control the robot and human-operator's visual attention patterns when teleoperating a robot from virtual reality.
A VR-based robot teleoperation framework was developed, it is compatible with various robotic systems and cameras, allowing for teleoperation and supervised control with any ROS-compatible robot and visualisation of the environment through any ROS-compatible RGB and RGBD cameras. The framework includes mapping, segmentation, tactile exploration, and non-physically demanding VR interface navigation and controls through any Unity-compatible VR headset and controllers or haptic devices.
Point clouds are a common way to visualise remote environments in 3D, but they often have distortions and occlusions, making it difficult to accurately represent objects' textures. This can lead to poor decision-making during teleoperation if objects are inaccurately represented in the VR reconstruction. A study using an end-effector-mounted RGBD camera with OctoMap mapping of the remote environment was conducted to explore the remote environment with fewer point cloud distortions and occlusions while using a relatively small bandwidth. Additionally, a tactile exploration study proposed a novel method for visually presenting information about objects' materials in the VR interface, to improve the operator's decision-making and address the challenges of point cloud visualisation.
Two studies have been conducted to understand the effect of virtual world dynamic scaling on teleoperation flow. The first study investigated the use of rate mode control with constant and variable mapping of the operator's joystick position to the speed (rate) of the robot's end-effector, depending on the virtual world scale. The results showed that variable mapping allowed participants to teleoperate the robot more effectively but at the cost of increased perceived workload.
The second study compared how operators used a virtual world scale in supervised control, comparing the virtual world scale of participants at the beginning and end of a 3-day experiment. The results showed that as operators got better at the task they as a group used a different virtual world scale, and participants' prior video gaming experience also affected the virtual world scale chosen by operators.
Similarly, the human-operator's visual attention study has investigated how their visual attention changes as they become better at teleoperating a robot using the framework.
The results revealed the most important objects in the VR reconstructed remote environment as indicated by operators' visual attention patterns as well as their visual priorities shifts as they got better at teleoperating the robot. The study also demonstrated that operators’ prior video gaming experience affects their ability to teleoperate the robot and their visual attention behaviours
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