6,530 research outputs found
Information management in an integrated space telerobot
The in-orbit operations, like space structures inspection, servicing and repairing, is expected to be one of the most significant technological area for application and development of Robotics and Automation in Space Station environment. The Italian National Space Plan (PSN) has started up its strategic programme SPIDER (Space Inspection Device for Extravehicular Repairs), which is scheduled in three phases, with the final goal of performing docking and precision repairing in the Space Station environment. SPIDER system is an autonomous integrated space robot, using mature Artificial Intelligence tools and technics for its operational control. The preliminary results of a study on the information architecture of the spacecraft are described
Editorial: Special issue on ground robots operating in dynamic, unstructured and large-scale outdoor environments
Real-world outdoor applications of ground robots have, to date, been limited primarily to remote inspection of suspected explosive devices and, with less success, to the broader domain of remote survey and inspection in hazardous environments. Such robots have almost exclusively been tele-operated. Also notable as examples of outdoor ground robots are the planetary rovers, currently deployed with great success on the surface of Mars. But with the rapid development of autonomous (driverless) cars, and the emergence of robotic vehicles in agriculture, it is likely that there will be significant growth in both the numbers and scope of commercial ground robots in outdoor environments in the near future.For this special issue we called for papers that present land robot systems deployed in the field in similar realistic challenges. We sought papers that focus on any aspect of robotic systems, from vehicle design to the overall system architecture and control, via terrain mapping, localization, mission planning and execution â with an emphasis on systems that fulfil a specific real world task. We specified that robot or system innovations must be supported by extensive field results. Also that field tests must be under realistic and challenging conditions with respect to the terrain type, the scenario to be achieved, and/or the conditions within which the scenarios must be achieved
Vision and Learning for Deliberative Monocular Cluttered Flight
Cameras provide a rich source of information while being passive, cheap and
lightweight for small and medium Unmanned Aerial Vehicles (UAVs). In this work
we present the first implementation of receding horizon control, which is
widely used in ground vehicles, with monocular vision as the only sensing mode
for autonomous UAV flight in dense clutter. We make it feasible on UAVs via a
number of contributions: novel coupling of perception and control via relevant
and diverse, multiple interpretations of the scene around the robot, leveraging
recent advances in machine learning to showcase anytime budgeted cost-sensitive
feature selection, and fast non-linear regression for monocular depth
prediction. We empirically demonstrate the efficacy of our novel pipeline via
real world experiments of more than 2 kms through dense trees with a quadrotor
built from off-the-shelf parts. Moreover our pipeline is designed to combine
information from other modalities like stereo and lidar as well if available
Human Motion Trajectory Prediction: A Survey
With growing numbers of intelligent autonomous systems in human environments,
the ability of such systems to perceive, understand and anticipate human
behavior becomes increasingly important. Specifically, predicting future
positions of dynamic agents and planning considering such predictions are key
tasks for self-driving vehicles, service robots and advanced surveillance
systems. This paper provides a survey of human motion trajectory prediction. We
review, analyze and structure a large selection of work from different
communities and propose a taxonomy that categorizes existing methods based on
the motion modeling approach and level of contextual information used. We
provide an overview of the existing datasets and performance metrics. We
discuss limitations of the state of the art and outline directions for further
research.Comment: Submitted to the International Journal of Robotics Research (IJRR),
37 page
Aspects of automation of selective cleaning
Cleaning (pre-commercial thinning) is a silvicultural operation, primarily used to improve growing conditions of remaining trees in young stands (ca. 3 - 5 m of height). Cleaning costs are considered high in Sweden and the work is laborious. Selective cleaning with autonomous artificial agents (robots) may rationalise the work, but requires new knowledge. This thesis aims to analyse key issues regarding automation of cleaning; suggesting general solutions and focusing on automatic selection of main-stems. The essential requests put on cleaning robots are to render acceptable results and to be cost competitive. They must be safe and be able to operate independently and unattended for several hours in a dynamic and non-deterministic environment. Machine vision, radar, and laser scanners are promising techniques for obstacle avoidance, tree identification, and tool control. Horizontal laser scannings were made, demonstrating the possibility to find stems and make estimations regarding their height and diameter. Knowledge regarding stem selections was retrieved through qualitative interviews with persons performing cleaning. They consider similar attributes of trees, and these findings and current cleaning manuals were used in combination with a field inventory in the development of a decision support system (DSS). The DSS selects stems by the attributes species, position, diameter, and damage. It was used to run computer-based simulations in a variety of young forests. A general follow-up showed that the DSS produced acceptable results. The DSS was further evaluated by comparing its selections with those made by experienced cleaners, and by a test in which laymen performed cleanings following the system. The DSS seems to be useful and flexible, since it can be adjusted in accordance with the cleanersâ results. The laymenâs results implied that the DSS is robust and that it could be used as a training tool. Using the DSS in automatic, or semi-automatic, cleaning operations should be possible if and when selected attributes can be automatically perceived. A suitable base-machine and thorough research, regarding e.g. safety, obstacle avoidance, and target identification, is needed to develop competitive robots. However, using the DSS as a training-tool for inexperienced cleaners could be an interesting option as of today
Watch Your Step! Terrain Traversability for Robot Control
Watch your step! Or perhaps, watch your wheels. Whatever the robot is, if it puts its feet, tracks, or wheels in the wrong place, it might get hurt; and as robots are quickly going from structured and completely known environments towards uncertain and unknown terrain, the surface assessment becomes an essential requirement. As a result, future mobile robots cannot neglect the evaluation of terrainâs structure, according to their driving capabilities. With the objective of filling this gap, the focus of this study was laid on terrain analysis methods, which can be used for robot control with particular reference to autonomous vehicles and mobile robots. Giving an overview of theory related to this topic, the investigation not only covers hardware, such as visual sensors or laser scanners, but also space descriptions, such as digital elevation models and point descriptors, introducing new aspects and characterization of terrain assessment. During the discussion, a wide number of examples and methodologies are exposed according to different tools and sensors, including the description of a recent method of terrain assessment using normal vectors analysis. Indeed, normal vectors has demonstrated great potentialities in the field of terrain irregularity assessment in both onâroad and offâroad environments
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