Motion control

Résumé

Motion control is a sub-field of automation, encompassing the systems or sub-systems involved in moving parts of machines in a controlled manner. Motion control systems are extensively used in a variety of fields for automation purposes, including precision engineering, micromanufacturing, biotechnology, and nanotechnology. The main components involved typically include a motion controller, an energy amplifier, and one or more prime movers or actuators. Motion control may be open loop or closed loop. In open loop systems, the controller sends a command through the amplifier to the prime mover or actuator, and does not know if the desired motion was actually achieved. Typical systems include stepper motor or fan control. For tighter control with more precision, a measuring device may be added to the system (usually near the end motion). When the measurement is converted to a signal that is sent back to the controller, and the controller compensates for any error, it becomes a Closed lo

Source officielle

https://en.wikipedia.org/wiki/Motion_control

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This course is a real contact with industrial robotic applications. Components and mechanisms are reminded. The fields of microtechnical assembly and packaging are treated. CTOs from established companies (BlueBotics, Adept, Maxon motors and UniTechnologies) are involved in this course.

This course teaches basic knowledge on haptic devices, force feedback and mechanical man-machine interfaces. Lectures are about 40 %, the rest is hands-on practical work with the "haptic paddle", a complete mechanical device with full laptop control interface. Realization of project in groups of 2.

This course consists of two parts:

architecture of automation systems, hands-on lab
handling of faults and failures in real-time systems, including fault-tolerant computing

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Séances de cours associées (5)

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Recent advances in Model Predictive Control (MPC) algorithms and methodologies, combined with the surge of computational power of available embedded platforms, allows the use of real-time optimization-based control of fast mechatronic systems. This paper presents an implementation of an optimal guidance, navigation and control (GNC) system for the motion control of a small-scale electric prototype of a thrust-vectored rocket. The aim of this prototype is to provide an inexpensive platform to explore GNC algorithms for automatic landing of sounding rockets. The guidance and trajectory tracking are formulated as continuous-time optimal control problems and are solved in real-time on embedded hardware using the PolyMPC library. An Extended Kalman Filter (EKF) is designed to estimate external disturbances and actuators offsets. Finally, indoor and outdoor flight experiments are performed to validate the architecture.

2021

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Autonomous drone racing (ADR) is a challenge for autonomous drones to navigate a cluttered indoor environment without relying on any external sensing in which all the sensing and computing must be done with onboard resources. Although no team could complete the whole racing track so far, most successful teams implemented waypoint tracking methods and robust visual recognition of the gates of distinct colors because the complete environmental information was given to participants before the events. In this paper, we introduce the purpose of ADR as a benchmark testing ground for autonomous drone technologies and analyze challenges and technologies used in the two previous ADRs held in IROS 2016 and IROS 2017. Five teams which participated in these events present their implemented technologies that cover modified ORB-SLAM, robust alignment method for waypoints deployment, sensor fusion for motion estimation, deep learning for gate detection and motion control, and stereo-vision for gate detection.

2019

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Motion control for human animation

EPFL1997

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