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Algorithm Controls

interview by   -   July 23, 2016


In this episode, Audrow Nash interviews Emo Todorov, Director of Movement Control Laboratory at the University of Washington, about a physics-based optimization method for controlling robots. Todorov describes how his physics-based method can be used to solve problems and discusses results in simulation and on hardware.

interview by   -   July 9, 2016

In this episode, Audrow Nash interviews Karl Iagnemma, a Principal Research Scientist at the Massachusetts Institute of Technology and the CEO of nuTonomy, about autonomous vehicles in urban environments. Iagnemma discusses the market for autonomous cars, why nuTonomy is being developed and, at least initially, deployed in Singapore, and the technology of autonomous cars.

by   -   February 22, 2016

Last week Raffaello D’Andrea, professor at the Swiss Federal Institute of Technology (ETH Zurich) and founder of Verity Studios, demonstrated a whole series of novel flying machines live on stage at TED2016: From a novel Tail-Sitter (a small, fixed-wing aircraft that can optimally recover a stable flight position after a disturbance and smoothly transition from hover into forward flight and back), to the “Monospinner” (the world’s mechanically simplest flying machine, with only a single moving part), to the “Omnicopter” (the world’s first flying machine that can move into any direction independent of its orientation and its rotation), to a novel fully redundant quadrocopter (the world’s first, consisting of two separate two-propeller flying machines), to a synthetic swarm (33 flying machines swarming above the audience).

by ,   -   January 27, 2016

The idea of connecting brain-inspired models of computation to robots is probably as old as the discipline of robotics itself. Today, researchers are connecting robotics with neuroscience in order to both build intelligent robots and to better understand the brain. The workshop Advances in Biologically Inspired Brain-Like Cognition and Control for Learning Robots at IROS (Hamburg) brought together experts from diverse fields in brain-based robotics, neurorobotics, artificial neural networks and machine learning to discuss the state of the art.

by   -   January 19, 2016

Getting drones to fly around without hitting things is no small task. Obstacle-detection and motion-planning are two of computer science’s trickiest challenges because of the complexity involved in creating real-time flight plans that avoid obstacles and handle surprises like wind and weather. In a pair of projects announced this week, CSAIL researchers demonstrated software that allow drones to stop on a dime to make hairpin movements over, under, and around some 26 distinct obstacles in a simulated “forest.”

by   -   January 5, 2016

The Flying Platform is a new flying machine developed at the Institute for Dynamic Systems and Control at ETH Zurich. Its purpose is to study the use of electric ducted fans as control and propulsion systems for flying machines in applications where size is limited and high static thrusts are required, for example in aerial vehicles capable of vertical take-off and landing (VTOL), hovercrafts or even actuated wingsuit flight. The video below shows how the thrust vectoring is used to stabilize the vehicle.

by   -   September 29, 2015

In this new lecture series, controls expert Brian Douglas walks you through key concepts in control system theory. Focused on making control theory accessible and intuitive, this series is for anyone who wants to relate control concepts to robotic applications in the real world.

interview by   -   September 4, 2015

Flying Fotokite close up

by   -   June 4, 2015

Researchers at ETH Zurich have developed a new algorithm for robustly controlling a tailsitter flying machine in hover position. Using the algorithm, the tailsitter is able to recover from any orientation, including upside down.

by   -   May 5, 2015

High-g-quadrocopter-trainingThis video shows tethered quadrocopters flying steadily together at high speeds exceeding 50 km/h in a confined space. With the tether exerting more than 13 gs of centripetal force, multiple quadrotors are able to fly 1.7m- radius circular trajectories in formation across different orientations in space and then successfully perform a coordinated braking maneuver.

by   -   April 21, 2015
Komekurayama Solar Power Plant owned and operated by TEPCO in Kofu, Yamanashi Prefecture. Source: Sakaori via Wikimedia Commons.
Komekurayama Solar Power Plant owned and operated by TEPCO in Kofu, Yamanashi Prefecture. Source: Sakaori via Wikimedia Commons.

Japan’s power industry is currently centralized, but it aims to deregulate by around 2020. Coupled with this major structural market change, the expansion of thermal, nuclear and renewable power generation will place additional demands on the management of the country’s energy market. Researchers from the Namerikawa lab at Keio University are working with control engineers, power engineers and economists to designing mechanical and control algorithms that can manage this large-scale problem.

by   -   October 15, 2014

We have developed a visually controlled bipedal running robot named ACHIRES: Actively Coordinated High-speed Image-processing Running Experiment System. This robot has a leg length of 14cm and 6 degrees of freedom, and can run in the sagittal plane at 4.2 km/h . Its key technologies are high-speed vision for recognizing the posture of the robot at 600 fps, and high-speed actuation for realizing high speed motion. The combination of these technologies plays an important role in the robot’s ability to run stably at high speeds.

by   -   October 8, 2014

Ant Intelligent Robot (AIR) is a small and powerful mobile robot platform that is designed to be used in a heterogeneous robotic swarm that is currently under development at the Laboratory of Artificial Intelligence and Multi-Agent Systems (AI-MAS) at the University “Politehnica” of Bucharest under the supervision of Prof. Adina Magda Florea. I made this video to depict the major development stages of the project.


Last December, an article named “Playing Atari with Deep Reinforcement Learning” was uploaded to arXiv by employees of a small AI company called DeepMind. Two months later Google bought DeepMind for 500 million euros, and this article is almost the only thing we know about the company . Currently our team is trying to replicate their artificial mind, and in this post we describe its inner workings.

by   -   September 22, 2014

The dance between human and machine has never looked quite like this.

May 16, 2014

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