Author name cluster

Markus Hehn

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

8 papers

1 author row

IROS Conference 2013 Conference Paper

A computationally efficient algorithm for state-to-state quadrocopter trajectory generation and feasibility verification

Mark W. Mueller
Markus Hehn
Raffaello D'Andrea

An algorithm is proposed allowing for the rapid generation and evaluation of quadrocopter state interception trajectories. These trajectories are from arbitrary initial states to final states defined by the vehicle position, velocity and acceleration with a specified end of time. Sufficient criteria are then derived allowing trajectories to be tested for feasibility with respect to thrust and body rates. It is also shown that the range of a linear combination of the vehicle state can be solved for in closed form, useful e. g. for testing that the position remains within a box. The algorithm is applied by revisiting the problem of finding a trajectory to hit a ball towards a target with a racket attached to a quadrocopter. The trajectory generator is used in a model predictive control like strategy, where thousands of trajectories are generated and evaluated at every controller update step, with the first input of the optimal trajectory being sent to the vehicle. It is shown that the method can generate and evaluate on the order of one million trajectories per second on a standard laptop computer.

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IROS Conference 2013 Conference Paper

A frequency domain iterative feed-forward learning scheme for high performance periodic quadrocopter maneuvers

Markus Hehn
Raffaello D'Andrea

Quadrocopters exhibit complex high-speed fight dynamics, and the accurate modeling of these dynamics has proven diffcult. Due to the use of simplifed models in the design of feedback control algorithms, the execution of highperformance fight maneuvers under pure feedback control typically leads to large tracking errors. This paper investigates an iterative learning scheme aimed at the non-causal compensation of repeatable trajectory tracking errors over the course of multiple executions of periodic maneuvers. The learning is carried out in the frequency domain and uses a simplifed model of the closed-loop dynamics of quadrocopter and feedback controller. The resulting algorithm requires little computational power and memory, and its convergence is shown for the nominal model. This paper further introduces a time-scaling method that allows the initial learning to occur at reduced speeds, thus extending the applicability of the algorithm for high performance maneuvers. The presented algorithms are validated in experiments, with a quadrocopter fying a fgure-eight maneuver at high speed.

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IROS Conference 2013 Conference Paper

Quadrocopter pole acrobatics

Dario Brescianini
Markus Hehn
Raffaello D'Andrea

We present the design of a system that allows quadrocopters to balance an inverted pendulum, throw it into the air, and catch and balance it again on a second vehicle. Based on first principles models, a launch condition for the pole is derived and used to design an optimal trajectory to throw the pole towards a second quadrocopter. An optimal catching instant is derived and the corresponding position is predicted by simulating the current position and velocity estimates forward in time. An algorithm is introduced that generates a trajectory for moving the catching vehicle to the predicted catching point in real time. By evaluating the pole state after the impact, an adaptation strategy adapts the catch maneuver such that the pole rotates into the upright equilibrium by itself. Experimental results demonstrate the performance of the system.

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IROS Conference 2012 Conference Paper

Cooperative quadrocopter ball throwing and catching

Robin Ritz
Mark W. Mueller
Markus Hehn
Raffaello D'Andrea

This paper presents a method for enabling a fleet of circularly arranged quadrocopters to throw and catch balls with a net. Based on a first-principles model of the net forces, nominal inputs for all involved vehicles are derived for arbitrary target trajectories of the net. Two algorithms that generate open-loop trajectories for throwing and catching a ball are also introduced. A set of throws and catches is demonstrated in the ETH Zurich Flying Machine Arena testbed.

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IROS Conference 2012 Conference Paper

Real-time trajectory generation for interception maneuvers with quadrocopters

Markus Hehn
Raffaello D'Andrea

This paper presents an algorithm that permits the calculation of interception maneuvers for quadrocopters. The translational degrees of freedom of the quadrocopter are decoupled. Pontryagin's minimum principle is used to show that the interception maneuver that minimizes the time to rest after the interception is identical to the time-optimal maneuver that drives the vehicle to the position at which it comes to rest after the interception. This fact is leveraged to apply previously developed, computationally efficient methods for the computation of interception maneuvers. The resulting trajectory generation algorithm is computationally lightweight, permitting its use as an implicit feedback law by replanning the trajectory at each controller update. The validity and performance of the approach is demonstrated experimentally by intercepting balls mid-flight. The real-time trajectory generation permits to take into account changes in the predicted ball flight path at each controller update.

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ICRA Conference 2011 Conference Paper

A flying inverted pendulum

Markus Hehn
Raffaello D'Andrea

We extend the classic control problem of the inverted pendulum by placing the pendulum on top of a quadrotor aerial vehicle. Both static and dynamic equilibria of the system are investigated to find nominal states of the system at standstill and on circular trajectories. Control laws are designed around these nominal trajectories. A yaw-independent description of quadrotor dynamics is introduced, using a ‘Virtual Body Frame’. This allows for the time-invariant description of curved trajectories. The balancing performance of the controller is demonstrated in the ETH Zurich Flying Machine Arena testbed. Development potential for the future is highlighted, with a focus on applying learning methodology to increase performance by eliminating systematic errors that were seen in experiments.

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IROS Conference 2011 Conference Paper

Quadrocopter performance benchmarking using optimal control

Robin Ritz
Markus Hehn
Sergei Lupashin
Raffaello D'Andrea

A numerical method for computing quadrocopter maneuvers between two states is presented. Computed maneuvers satisfy Pontryagin's minimum principle with respect to time-optimality. First, in order to obtain the structure of time-optimal maneuvers, we apply the minimum principle to a first-principles, two-dimensional quadrotor model. Then we present a numerical algorithm that enables the computation of maneuvers for arbitrary initial and final states. The developed method is used to compute a set of maneuvers, which are discussed and demonstrated experimentally in the ETH Zurich Flying Machine Arena testbed.

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ICRA Conference 2011 Conference Paper

The Flying Machine Arena as of 2010

Sergei Lupashin
Angela P. Schoellig
Markus Hehn
Raffaello D'Andrea

The Flying Machine Arena (FMA) is an indoor research space built specifically for the study of autonomous systems and aerial robotics. In this video, we give an overview of this testbed and some of its capabilities. We show the FMA infrastructure and hardware, which includes a fleet of quadrocopters and a motion capture system for vehicle localization. The physical components of the FMA are complemented by specialized software tools and components that facilitate the use of the space and provide a unified framework for communication and control. The flexibility and modularity of the experimental platform is highlighted by various research projects and demonstrations.

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