Global asymptotic stabilization of spherical orientation by synergistic hybrid feedback with application to reduced attitude synchronization
We develop a hybrid controller for global asymptotic stabilization
on the n-dimensional sphere using synergistic potential functions.
These consist of a collection of potential functions that induce a
gradient descent controller during flows of the hybrid closed-loop
system and a switching law that, at undesired equilibrium points
of the gradient vector field, jumps to the lowest value among all
the potential functions in the collection. We show that the proposed
controller can be used for global reduced attitude synchronization,
i.e., given a network of rigid-bodies, the proposed synergistic hybrid
feedback can be used to globally synchronize a reference direction
of each agent within a global but unknown inertial reference frame.
We study this application for a network of three vehicles by means
of simulation results.
Pedro Casau is a Research Assistant at the SCORE Lab of the
Faculty of Science and Technology, University of Macau. He
received received the B.Sc. in Aerospace Engineering in 2008
from Instituto Superior Técnico (IST), Lisbon, Portugal. In 2010,
he received the M.Sc. in Aerospace Engineering from IST and
enrolled in the Electrical and Computer Engineering Ph.D.
program at the same institution which he completed with
distinction and honours in 2016. While at IST, he participated
on several national and international research projects on
guidance, navigation and control of unmanned air vehicles
(UAVs) and satellites. His current research interests include
nonlinear control, hybrid control systems, vision-based control
systems, controller design for autonomous air-vehicles.
Mechatronics Public Demo!
Watch robots compete in the Mechatronics Public Demo! Cheer on their sleep-deprived creators as they run their ‘bots through the field. Thrill to battles between autonomous robots navigating the field, dodging obstacles, and scoring points by shooting their ping pong ball ammo at the opponent robot! Come see this exciting SLUGNIFICANT SEVEN competition!
What: CMPE118 Mechatronics Public Demo
Where: UCSC Media Theater (M110)
When: Friday 7-Dec-2018, 6:15 - 8:30PM
The Mechatronics class is having their public demonstration of their final design project, SLUGNIFICANT SEVEN, Friday 7-Dec-2018 at 6:15 PM in the UCSC Media Theater (M110).
In this thrilling competition, teams from UCSC's Mechatronics course will pit their autonomous robots against each other in an epic SLUGNIFICANT SEVEN duel. Each robotic champion will begin back to back, then race to the initial firing zone at the other end of the field. From there, they can either destroy their opponent with ping pong ball ammo, or advance to a better firing position by hiding behind the obstacles. The champions will compete in a wild head to head tournament, until only one robot emerges victorious!
The public is invited (you might have to duck a few ping-pong balls) and the teams will be on hand to explain their designs to one and all. Come see what these students have accomplished in 10 weeks and cheer on the competition.
There will be a live webcast starting at 6PM:
www.twitch.tv/elkaim_ucsc (close up of the field)
www.twitch.tv/mdunneucsc (wide view of room)
Feel free to forward this to any and all that might be interested, children (future engineers) especially welcome.
CPSRC Seminar Series - Ants Don't Use WiFi: Enabling Robotic Agents to Collaborate and Compete without a Communication Network
In the animal world there is no WiFi---agents collaborate and compete by sensing and predicting the actions of teammates, rivals, predators, and prey. Likewise, in the engineered world, many of the most promising applications for autonomous robots require them to interact with other agents in the world by sensing and predicting their actions. Autonomous driving in traffic, collision avoidance for UAVs, and human-robot teaming are key examples where a wireless network either cannot exist, or will not exist for some time. In competitive scenarios, such as racing or pursuit-evasion, agents would not want to communicate even if they could. In this talk I will describe several recent examples from my lab of algorithms enabling multiple robotic agents to interact, both collaboratively and competitively, without a communication network. I will discuss a communication-free multi-robot manipulation algorithm by which many simple robots cooperate to transport a payload too large for any one of them to move alone. I will describe a highly scalable collision avoidance strategy, and a related pursuit-evasion strategy, that only requires agents to sense the positions of nearby neighbors. Finally, I will present a game theoretic receding horizon control algorithm for autonomous drone racing, in which drones sense each other's position with a monocular camera. I will show results from hardware experiments with ground robots, scale autonomous cars, and quadrotor UAVs collaborating and competing in the scenarios above.
Mac Schwager is an assistant professor of Aeronautics and Astronautics at Stanford University. He directs the Multi-robot Systems Lab (MSL) where he studies distributed algorithms for control, perception, and learning in groups of robots and autonomous systems. He is interested in a range of applications including cooperative surveillance with teams of UAVs, agile formation control and collision avoidance for UAVs, autonomous driving in traffic, cooperative robotic manipulation, and autonomous drone racing. He obtained his BS degree from Stanford, and his MS and PhD degrees from MIT. He was a postdoctoral researcher in the GRASP lab at the University of Pennsylvania, and in CSAIL at MIT. Prior to joining Stanford, he was an assistant professor at Boston University from 2012 to 2015. He received the NSF CAREER award in 2014, the DARPA YFA in 2018, and has received numerous best paper awards in conferences and journals including the IEEE Transactions on Robotics King-Sun Fu best paper award in 2016.
CPSRC Seminar Series - Temporal Logic Robustness: Applications to Synthesis and Analysis of Autonomous Systems
Many autonomous (or highly automated) systems are also safety critical. Due to their safety critical nature, they must adhere to well defined requirements typically in pairs of assumptions and guarantees. An ongoing research challenge is to develop a specification formalism to rule them all. That is, the formalism has to be expressive enough to capture all requirements of interest while at the same time it has to be computationally efficient in order to be used in automated analysis and design. Temporal logics have proven to be an excellent choice when considering their expressive power and computational efficiency. In this talk, we will review the theory of robustness of temporal logics as applied to Cyber-Physical Systems (CPS). We will highlight the connections between synthesis and analysis methods with respect to temporal logic requirements and their robust interpretation. In addition, we will show how some verification and specification mining problems can be translated into optimization problems using the notion of robustness. In terms of applications, we will demonstrate how temporal logic requirements can help us in automated testing of autonomous vehicles and perception systems, and in the planning and coordination of groups of vehicles under different access right levels.
Georgios Fainekos is an Associate Professor at the School of Computing, Informatics and Decision Systems Engineering (SCIDSE) at Arizona State University (ASU). He is director of the Cyber-Physical Systems (CPS) Lab and he is currently affiliated with the NSF I/UCR Center for Embedded Systems (CES) and the Robotics Faculty Group at ASU. He received his Ph.D. in Computer and Information Science from the University of Pennsylvania in 2008 where he was affiliated with the GRASP laboratory. He holds a Diploma degree (B.Sc. & M.Sc.) in Mechanical Engineering from the National Technical University of Athens (NTUA). Before joining ASU, he held a Postdoctoral Researcher position at NEC Laboratories America in the System Analysis & Verification Group. His technical expertise is on applied logic, formal verification, testing, control theory, artificial intelligence, and optimization. His research has applications to automotive systems, medical devices, autonomous (ground and aerial) vehicles, and human-robot interaction (HRI). In 2013, Dr. Fainekos received the NSF CAREER award and the ASU SCIDSE Best Researcher Junior Faculty Award. He is also recipient of the 2008 Frank Anger Memorial ACM SIGBED/SIGSOFT Student Award. His software toolbox, S-TaLiRo, for testing and monitoring of CPS has been nominated twice as a technological breakthrough by the industry. In 2016, Dr. Fainekos was the program co-Chair for the ACM International Conference on Hybrid Systems: Computation and Control (HSCC).
From Shakey to Motobot: Robotics at SRI International
SRI researchers have a rich tradition of pushing the boundaries of robotics. Our heritage includes Shakey, the first intelligent mobile robot, the foundational telepresence technology used in Intuitive Surgical's DaVinci surgical system, and electroactive polymer "artificial muscle" for bio-inspired robots. SRI has continued to innovate in several areas of robotics ranging from intelligent system to new components and materials. This talk will highlight our recent work in electroactive materials for soft robotics, massively parallel manufacturing using diamagnetically-levitated microrobots, electroadhesive gripping, next-generation telepresence manipulation, wearable robotics, and breakthrough work in more efficient and infinitely variable mechanical transmissions. We will also show the successors to Shakey: Motobot - a robot that can race a stock motor cycle, Proxy - a biologically-inspired robot that walks efficiently, and an apple-picking robot now being commercialized by Abundant robotics.
The presentation will be given by the researchers in SRI's Robotics Laboratory who have led the efforts described above. These presenters include: Roy Kornbluh, Annjoe Wong-Foy, Allen Hsu, Thomas Low, Alexander Kernbaum and Gordon Kirkwood.