8,493 research outputs found
The sensing and perception subsystem of the NASA research telerobot
A useful space telerobot for on-orbit assembly, maintenance, and repair tasks must have a sensing and perception subsystem which can provide the locations, orientations, and velocities of all relevant objects in the work environment. This function must be accomplished with sufficient speed and accuracy to permit effective grappling and manipulation. Appropriate symbolic names must be attached to each object for use by higher-level planning algorithms. Sensor data and inferences must be presented to the remote human operator in a way that is both comprehensible in ensuring safe autonomous operation and useful for direct teleoperation. Research at JPL toward these objectives is described
Assembly via disassembly: A case in machine perceptual development
First results in the effort of learning about representations of objects is presented. The questions attempted to be answered are: What is innate and what must be derived from the environment. The problem is casted in the framework of disassembly of an object into two parts
Study of optical techniques for the Ames unitary wind tunnels. Part 4: Model deformation
A survey of systems capable of model deformation measurements was conducted. The survey included stereo-cameras, scanners, and digitizers. Moire, holographic, and heterodyne interferometry techniques were also looked at. Stereo-cameras with passive or active targets are currently being deployed for model deformation measurements at NASA Ames and LaRC, Boeing, and ONERA. Scanners and digitizers are widely used in robotics, motion analysis, medicine, etc., and some of the scanner and digitizers can meet the model deformation requirements. Commercial stereo-cameras, scanners, and digitizers are being improved in accuracy, reliability, and ease of operation. A number of new systems are coming onto the market
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Real-time spatial modeling to detect and track resources on construction sites
For more than 10 years the U.S. construction industry has experienced over 1,000
fatalities annually. Many fatalities may have been prevented had the individuals and
equipment involved been more aware of and alert to the physical state of the environment
around them. Awareness may be improved by automatic 3D (three-dimensional) sensing
and modeling of the job site environment in real-time. Existing 3D modeling approaches
based on range scanning techniques are capable of modeling static objects only, and thus
cannot model in real-time dynamic objects in an environment comprised of moving
humans, equipment, and materials. Emerging prototype 3D video range cameras offer
another alternative by facilitating affordable, wide field of view, automated static and
dynamic object detection and tracking at frame rates better than 1Hz (real-time).
This dissertation presents an imperical work and methodology to rapidly create a
spatial model of construction sites and in particular to detect, model, and track the position, dimension, direction, and velocity of static and moving project resources in real-time, based on range data obtained from a three-dimensional video range camera in a
static or moving position. Existing construction site 3D modeling approaches based on
optical range sensing technologies (laser scanners, rangefinders, etc.) and 3D modeling
approaches (dense, sparse, etc.) that offered potential solutions for this research are
reviewed. The choice of an emerging sensing tool and preliminary experiments with this
prototype sensing technology are discussed. These findings led to the development of a
range data processing algorithm based on three-dimensional occupancy grids which is
demonstrated in detail. Testing and validation of the proposed algorithms have been
conducted to quantify the performance of sensor and algorithm through extensive
experimentation involving static and moving objects. Experiments in indoor laboratory
and outdoor construction environments have been conducted with construction resources
such as humans, equipment, materials, or structures to verify the accuracy of the
occupancy grid modeling approach. Results show that modeling objects and measuring
their position, dimension, direction, and speed had an accuracy level compatible to the
requirements of active safety features for construction. Results demonstrate that video
rate 3D data acquisition and analysis of construction environments can support effective
detection, tracking, and convex hull modeling of objects. Exploiting rapidly generated
three-dimensional models for improved visualization, communications, and process
control has inherent value, broad application, and potential impact, e.g. as-built vs. as-planned comparison, condition assessment, maintenance, operations, and construction
activities control. In combination with effective management practices, this sensing
approach has the potential to assist equipment operators to avoid incidents that result in
reduce human injury, death, or collateral damage on construction sites.Civil, Architectural, and Environmental Engineerin
Integrated process of images and acceleration measurements for damage detection
The use of mobile robots and UAV to catch unthinkable images together with on-site global automated acceleration measurements easy achievable by wireless sensors, able of remote data transfer, have strongly enhanced the capability of defect and damage evaluation in bridges. A sequential procedure is, here, proposed for damage monitoring and bridge condition assessment based on both: digital image processing for survey and defect evaluation and structural identification based on acceleration measurements. A steel bridge has been simultaneously inspected by UAV to acquire images using visible light, or infrared radiation, and monitored through a wireless sensor network (WSN) measuring structural vibrations. First, image processing has been used to construct a geometrical model and to quantify corrosion extension. Then, the consistent structural model has been updated based on the modal quantities identified using the acceleration measurements acquired by the deployed WSN. © 2017 The Authors. Published by Elsevier Ltd
Vision technology/algorithms for space robotics applications
The thrust of automation and robotics for space applications has been proposed for increased productivity, improved reliability, increased flexibility, higher safety, and for the performance of automating time-consuming tasks, increasing productivity/performance of crew-accomplished tasks, and performing tasks beyond the capability of the crew. This paper provides a review of efforts currently in progress in the area of robotic vision. Both systems and algorithms are discussed. The evolution of future vision/sensing is projected to include the fusion of multisensors ranging from microwave to optical with multimode capability to include position, attitude, recognition, and motion parameters. The key feature of the overall system design will be small size and weight, fast signal processing, robust algorithms, and accurate parameter determination. These aspects of vision/sensing are also discussed
Virtual Reality via Object Pose Estimation and Active Learning:Realizing Telepresence Robots with Aerial Manipulation Capabilities
This paper presents a novel telepresence system for advancing aerial manipulation indynamic and unstructured environments. The proposed system not only features a haptic device, but also a virtual reality (VR) interface that provides real-time 3D displays of the robot’s workspace as well as a haptic guidance to its remotely located operator. To realize this, multiple sensors, namely, a LiDAR, cameras, and IMUs are utilized. For processing of the acquired sensory data, pose estimation pipelines are devised for industrial objects of both known and unknown geometries. We further propose an active learning pipeline in order to increase the sample efficiency of a pipeline component that relies on a Deep Neural Network (DNN) based object detector. All these algorithms jointly address various challenges encountered during the execution of perception tasks in industrial scenarios. In the experiments, exhaustive ablation studies are provided to validate the proposed pipelines. Method-ologically, these results commonly suggest how an awareness of the algorithms’ own failures and uncertainty (“introspection”) can be used to tackle the encountered problems. Moreover, outdoor experiments are conducted to evaluate the effectiveness of the overall system in enhancing aerial manipulation capabilities. In particular, with flight campaigns over days and nights, from spring to winter, and with different users and locations, we demonstrate over 70 robust executions of pick-and-place, force application and peg-in-hole tasks with the DLR cable-Suspended Aerial Manipulator (SAM). As a result, we show the viability of the proposed system in future industrial applications
Rapid 3D Modeling and Parts Recognition on Automotive Vehicles Using a Network of RGB-D Sensors for Robot Guidance
This paper presents an approach for the automatic detection and fast 3D profiling of lateral body panels of vehicles. The work introduces a method to integrate raw streams from depth sensors in the task of 3D profiling and reconstruction and a methodology for the extrinsic calibration of a network of Kinect sensors. This sensing framework is intended for rapidly providing a robot with enough spatial information to interact with automobile panels using various tools. When a vehicle is positioned inside the defined scanning area, a collection of reference parts on the bodywork are automatically recognized from a mosaic of color images collected by a network of Kinect sensors distributed around the vehicle and a global frame of reference is set up. Sections of the depth information on one side of the vehicle are then collected, aligned, and merged into a global RGB-D model. Finally, a 3D triangular mesh modelling the body panels of the vehicle is automatically built. The approach has applications in the intelligent transportation industry, automated vehicle inspection, quality control, automatic car wash systems, automotive production lines, and scan alignment and interpretation
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