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The prospect of controlling devices merely by the power of one’s thoughts is compelling, especially for assistive technology applications. In the accompanying video, we show how we have strived to push brain–computer interface (BCI) technology out of the lab and into the real world, while simultaneously moving away from testing solely with healthy subjects to undertaking trials with patients and potential end–users. We describe the evolution of the motor imagery based BCI, which has resulted in a major milestone: the first patient trial of a motor imagery based BCI controlled wheelchair.
Posted on: October 9, 2012
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Vision sensors whose pixels asynchronously generate informative output events are gathering increasing interest because they can reduce the data latency, rate, and redundancy, while also increasing dynamic range. This paper proposes such a dynamic vision sensor (DVS) pixel which is aimed at color vision (cDVS). The pixel combines subthreshold continuous time analog circuits with event-driven switched capacitor amplifiers and asynchronous digital outputs. The cDVS simultaneously detects separate log-intensity and wavelength change events using a single buried double junction (BDJ) photodiode. Chip measurements show that the cDVS color change pathway can detect light wavelength changes as small as 15 nm while the cDVS relative intensity change pathway detects changes as small as 10% of intensity. The circuit is characterized and improvements are proposed. © 2011 IEEE.
Posted on: August 27, 2012
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Posted on: August 27, 2012
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We revisit a recently developed iterative learning algorithm that enables systems to learn from a repeated operation with the goal of achieving high tracking performance of a given trajectory. The learning scheme is based on a coarse dynamics model of the system and uses past measurements to iteratively adapt the feed-forward input signal to the system. The novelty of this work is an identification routine that uses a numerical simulation of the system dynamics to extract the required model information. This allows the learning algorithm to be applied to any dynamic system for which a dynamics simulation is available (including systems with underlying feedback loops). The proposed learning algorithm is applied to a quadrocopter system that is guided by a trajectory-following controller. With the identification routine, we are able to extend our previous learning results to three-dimensional quadrocopter motions and achieve significantly higher tracking accuracy due to the underlying feedback control, which accounts for nonrepetitive noise.
Posted on: August 27, 2012
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In the broader context of quadrupedal locomotion, this overview article introduces and compares two platforms that are similar in structure, size, and morphology, yet differ greatly in their concept of actuation. The first, ALoF, is a classically stiff actuated robot that is controlled kinematically, while the second, StarlETH, uses a soft actuation scheme based on highly compliant series elastic actuators. We show how this conceptual difference influences design and control of the robots, compare the hardware of the two systems, and show exemplary their advantages in different applications. © Oldenbourg Wissenschaftsverlag.
Posted on: August 27, 2012
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This paper investigates the mechanical benefits of employing a passive foot segment to improve energetic efficiency in legged running. The proposed lightweight design significantly reduces impact and damping losses, while simultaneously allowing for a natural-looking stance configuration. Actuator in- put and ankle spring properties were optimized in simulation and successfully tested in 2D running experiments.
Posted on: August 27, 2012
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This paper introduces StarlETH, a compliant quadrupedal robot that is designed to study fast, efficient, and versatile locomotion. The platform is fully actuated with high compliant series elastic actuation, making the system torque controllable and at the same time well suited for highly dynamic maneuvers. We additionally emphasize key elements of a powerful real time control and simulation environment. The work is concluded with a number of experiments that demonstrate the performance of the presented hardware and controllers.
Posted on: August 27, 2012
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This paper introduces a state estimation framework for legged robots that allows estimating the full pose of the robot without making any assumptions about the geometrical structure of its environment. This is achieved by means of an Observability Constrained Extended Kalman Filter that fuses kinematic encoder data with on-board IMU measurements. By including the absolute position of all footholds into the filter state, simple model equations can be formulated which accurately capture the uncertainties associated with the intermittent ground contacts. The resulting filter simultaneously estimates the position of all footholds and the pose of the main body. In the algorithmic formulation, special attention is paid to the consistency of the linearized filter: it maintains the same observability properties as the nonlinear system, which is a prerequisite for accurate state estimation. The presented approach is implemented in simulation and validated experimentally on an actual quadrupedal robot.
Posted on: August 27, 2012
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This paper introduces the concept of hybrid operational space control, a method that unifies kinematic tracking of individual joints with an inverse dynamics task space controller for the remainder of the robot. The proposed control strategy allows for a hierarchical task decomposition while simultaneously regulating the inner forces between the contact points. At the same time it improves fast tracking for compliant systems by means of appropriate low level position controllers. Introducing StarlETH, a compliant quadrupedal robot, the applicability of the controller and the hardware is demonstrated in realtime simulations and hardware experiments. We perform static walking in challenging terrain and show how the controller can combine precise and fast position control with robust and compliant interaction with the environment.
Posted on: August 27, 2012
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In this work we apply optimal control to create running gaits for the model of an electrically driven one legged hopper, and compare the results obtained for five different objective functions. By using high compliant series elastic actuators, the motions of joint and motor are decoupled, which allows the exploitation of natural dynamics. Depending on the cost function, this exploitation varies. Energy is injected at different points of time, the amplitude of actuator action changes significantly, and the optimal gear ratios differ by a factor of two. Variations are, however, comparable over a wide range of hopping heights and running velocities. Purely force-based cost functions prove to be ill-suited for such non-conservative systems, and it is shown that thermal electrical losses, in contrast to common belief, do not dominate energy expenditure. The numerical results are corroborated by detailed analytical considerations which give general insights into optimal excitation with electric actuators.
Posted on: August 27, 2012