We address the problem of executing tool-using manipulation skills in scenarios where the objects to be used may vary. We assume that point clouds of the tool and target object can be obtained, but no interpretation or further knowledge about these objects is provided. The system must interpret the point clouds and decide how to use the tool to complete a manipulation task with a target object; this means it must adjust motion trajectories appropriately to complete the task. We tackle three everyday manipulations: scraping material from a tool into a container, cutting, and scooping from a container. Our solution encodes these manipulation skills in a generic way, with parameters that can be filled in at runtime via queries to a robot perception module; the perception module abstracts the functional parts of the tool and extracts key parameters that are needed for the task. The approach is evaluated in simulation and with selected examples on a PR2 robot.
An integration procedure is essential for the development of modern industry allowing the improvement of manufacturing process. This paper describes the implementation of a workcell integration procedure for a recovered robot manipulator with the development of multiple tasks programming. The adopted methodology is based on the definition of a control architecture incorporating a supervision system. The interoperability between this system and the controller devices is guaranteed by using wireless communication network. This methodology was applied to the manufactured of automotive compressors and has lead to improved manufacturing parameters.
Concepts related to the development of reconfigurable manufacturing systems (RMS) and methodologies to provide the best practices in the processing industry and factory automation, such as system integration and web‐based technology, are major issues in designing next‐generation manufacturing systems (NGMS). Adaptable and integrable devices are crucial for the success of NGMS. In robotic cells the integration of manufacturing components is essential to accelerate system adaptability. Sensors, control architectures and communication technologies have contributed to achieving further agility in reconfigurable factories. In this work a web‐based robotic cell integration procedure is proposed to aid the identification of reconfigurable issues and requirements. This methodology is applied to an industrial robot manipulator to enhance system flexibility towards the development of a reconfigurable robotic platform
This paper presents the research developments for the global nonlinear control of an autonomous airship, covering the full flight envelope from hovering to aerodynamic flight. It focuses on the longitudinal control of the airship using two different Sliding Mode control techniques that are the classical sliding mode and the unit vector approach. The design methodologies for both techniques are presented along with some representative simulation results. I. Introduction A great interest in the utilization of unmanned aerial vehicles appeared in the last fifteen years, due to their potential application in varied tasks such as surveillance, advertising, monitoring, inspection, exploration, and research roles 2. A new and special attention has been given to the use of unmanned aerial vehicles in environmental applications, such as biodiversity , ecological, climatic, and agricultural research and monitoring, among others. The data gathered by UAVs can also be used in a complementary way concerning information obtained by satellites, balloons, manned aircraft or on ground. Most of these applications for environmental purposes have profiles that require maneuverable low altitude, low speed airborne data gathering platforms. The vehicle should ideally be able to hover above an area, present extended airborne capabilities for long duration studies, takeoff and land vertically without the need of runway infrastructures, have a large payload to weight ratio, among other requisites. For this scenario, lighter-than-air (LTA) vehicles are better suited than airplanes and helicopters 1 mainly because: they derive the largest part of their lift from aerostatic, rather than aerodynamic forces; they are safer and, in case of failure, present a graceful degradation; they are intrinsically of higher stability than other platforms. In this context, Project AURORA-Autonomous Unmanned Remote mOnitoring Robotic Airship-was proposed 2. AURORA focuses on the establishment of the technologies required to substantiate autonomous operation of unmanned robotic airships for environmental monitoring and aerial inspection missions. This includes sensing and processing infrastructures, control and guidance capabilities, and the ability to perform mission, navigation, and sensor deployment planning and execution. Aiming the autonomous airship goal, aerial platform positioning and path tracking should be assured by a control and navigation system. Such a system needs to cope with the highly nonlinear, flight-dependent and underactuated airship dynamics, ranging from the hovering flight (HF) to the aerodynamic flight (AF) or cruise flight. Hovering flight is defined here as a flight at low airspeed condition. Basically, two main approaches can be considered for the automatic control and navigation system of an airship. The first one relies on the linear control theory to design individual compensators to satisfy closed-loop
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