Linear multimodal actuation through discrete coupling

Due to technological limitations, robot actuators are often designed for specific tasks with narrow performance goals, whereas a wide range of behaviors is necessary for autonomous robots in uncertain complex environments. In an effort to increase the versatility of actuators, we introduce a new concept of multimodal actuation (MMA) that employs dynamic coupling in the form of clutches and brakes to change its mode of operation. The dynamic coupling allows motors and passive elements such as springs to be engaged and disengaged within a single actuator. We apply the concept to a linear series elastic actuator which uses friction brakes controlled online for the dynamic coupling. With this prototype, we are able to demonstrate several modes of operation including stiff position control, series elastic actuation as well as the possibility to store and release energy in a controlled manner for explosive tasks such as jumping. In this paper, we model the proposed concept of actuation and show a systematic performance analysis of the physical prototype that we developed in our laboratory. © 1996-2012 IEEE.

Linear multi-modal actuation through discrete coupling

Due to technological limitations robot actuators are often designed for specific tasks with narrow performance goals, whereas a wide range of output and behaviours is necessary for robots to operate autonomously in uncertain complex environments. We present a design framework that employs dynamic couplings in the form of brakes and clutches to increase the performance and diversity of linear actuators. The couplings are used to switch between a diverse range of discrete modes of operation within a single actuator. We also provide a design solution for miniaturized couplings that use dry friction to produce rapid switching and high braking forces. The couplings are designed so that once engaged or disengaged no extra energy is consumed. We apply the design framework and coupling design to a linear series elastic actuator (SEA) and show that this relatively simple implementation increases the performance and adds new behaviours to the standard design. Through a number of performance tests we are able to show rapid switching between a high and a low impedance output mode; that the actuator's spring can be charged to produce short bursts of high output power; and that the actuator has additional passive and rigid modes that consume no power once activated. Robots using actuators from this design framework would see a vast increase in their behavioural diversity and improvements in their performance not yet possible with conventional actuator design. © 2012 IEEE.

Exploiting passive dynamics for robot throwing task

Throwing is a complex and highly dynamic task. Humans usually exploit passive dynamics of their limbs to optimize their movement and muscle activation. In order to approach human throwing, we developed a double pendulum robotic platform. To introduce passivity into the actuated joints, clutches were included in the drive train. In this paper, we demonstrate the advantage of exploiting passive dynamics in reducing the mechanical work. However, engaging and disengaging the clutches are done in discrete fashions. Therefore, we propose an optimization approach which can deal with such discontinuities. It is shown that properly engaging/disengaging the clutches can reduce the mechanical work of a throwing task. The result is compared to the solution of fully actuated double pendulum, both in simulation and experiment. © 2012 IEEE.

Trajectory control based on discrete full-range dynamics

There has been an increasing interest in the use of mechanical dynamics, (e.g., assive, Elastic, And viscous dynamics) for energy efficient and agile control of robotic systems. Despite the impressive demonstrations of behavioural performance, The mechanical dynamics of this class of robotic systems is still very limited as compared to those of biological systems. For example, Passive dynamic walkers are not capable of generating joint torques to compensate for disturbances from complex environments. In order to tackle such a discrepancy between biological and artificial systems, We present the concept and design of an adaptive clutch mechanism that discretely covers the full-range of dynamics. As a result, The system is capable of a large variety of joint operations, including dynamic switching among passive, actuated and rigid modes. The main innovation of this paper is the framework and algorithm developed for controlling the trajectory of such joint. We present different control strategies that exploit passive dynamics. Simulation results demonstrate a significant improvement in motion control with respect to the speed of motion and energy efficiency. The actuator is implemented in a simple pendulum platform to quantitatively evaluate this novel approach.

Motor control optimization of compliant one-legged locomotion in rough terrain

While underactuated robotic systems are capable of energy efficient and rapid dynamic behavior, we still do not fully understand how body dynamics can be actively used for adaptive behavior in complex unstructured environment. In particular, we can expect that the robotic systems could achieve high maneuverability by flexibly storing and releasing energy through the motor control of the physical interaction between the body and the environment. This paper presents a minimalistic optimization strategy of motor control policy for underactuated legged robotic systems. Based on a reinforcement learning algorithm, we propose an optimization scheme, with which the robot can exploit passive elasticity for hopping forward while maintaining the stability of locomotion process in the environment with a series of large changes of ground surface. We show a case study of a simple one-legged robot which consists of a servomotor and a passive elastic joint. The dynamics and learning performance of the robot model are tested in simulation, and then transferred the results to the real-world robot. ©2007 IEEE.

Predictive entropy search for efficient global optimization of black-box functions

We propose a novel information-theoretic approach for Bayesian optimization called Predictive Entropy Search (PES). At each iteration, PES selects the next evaluation point that maximizes the expected information gained with respect to the global maximum. PES codifies this intractable acquisition function in terms of the expected reduction in the differential entropy of the predictive distribution. This reformulation allows PES to obtain approximations that are both more accurate and efficient than other alternatives such as Entropy Search (ES). Furthermore, PES can easily perform a fully Bayesian treatment of the model hyperparameters while ES cannot. We evaluate PES in both synthetic and real-world applications, including optimization problems in machine learning, finance, biotechnology, and robotics. We show that the increased accuracy of PES leads to significant gains in optimization performance.

Manopt, a matlab toolbox for optimization on manifolds

Optimization on manifolds is a rapidly developing branch of nonlinear optimization. Its focus is on problems where the smooth geometry of the search space can be leveraged to design effcient numerical algorithms. In particular, optimization on manifolds is well-suited to deal with rank and orthogonality constraints. Such structured constraints appear pervasively in machine learning applications, including low-rank matrix completion, sensor network localization, camera network registration, independent component analysis, metric learning, dimensionality reduction and so on. The Manopt toolbox, available at www.manopt.org, is a user-friendly, documented piece of software dedicated to simplify experimenting with state of the art Riemannian optimization algorithms. By dealing internally with most of the differential geometry, the package aims particularly at lowering the entrance barrier. © 2014 Nicolas Boumal.

Fixed-rank matrix factorizations and Riemannian low-rank optimization

Motivated by the problem of learning a linear regression model whose parameter is a large fixed-rank non-symmetric matrix, we consider the optimization of a smooth cost function defined on the set of fixed-rank matrices. We adopt the geometric framework of optimization on Riemannian quotient manifolds. We study the underlying geometries of several well-known fixed-rank matrix factorizations and then exploit the Riemannian quotient geometry of the search space in the design of a class of gradient descent and trust-region algorithms. The proposed algorithms generalize our previous results on fixed-rank symmetric positive semidefinite matrices, apply to a broad range of applications, scale to high-dimensional problems, and confer a geometric basis to recent contributions on the learning of fixed-rank non-symmetric matrices. We make connections with existing algorithms in the context of low-rank matrix completion and discuss the usefulness of the proposed framework. Numerical experiments suggest that the proposed algorithms compete with state-of-the-art algorithms and that manifold optimization offers an effective and versatile framework for the design of machine learning algorithms that learn a fixed-rank matrix. © 2013 Springer-Verlag Berlin Heidelberg.

Optimization of growth and fatty acid composition of a unicellular marine picoplankton, Nannochloropsis sp., with enriched carbon sources

A unicellular marine picoplankton, Nannochloropsis sp., was grown under CO2-enriched photoautotrophic or/and acetate-added mixotrophic conditions. Photoautotrophic conditions with enriched CO2 of 2800 mul CO2 l(-1) and aeration gave the highest biomass yield (634 mg dry wt l(-1)), the highest total lipid content (9% of dry wt), total fatty acids (64 mg g(-1) dry wt), polyunsaturated fatty acids (35% total fatty acids) and eicosapentaenoic acid (EPA, 20:5omega3) (16 mg g(-1) dry wt or 25% of total fatty acids). Mixotrophic cultures gave a greater protein content but less carbohydrates. Adding sodium acetate (2 mM) decreased the amounts of the total fatty acids and EPA. Elevation of CO2 in photoautotrophic culture thus enhances growth and raises the production of EPA in Nannochloropsis sp.

Optimization of control parameters for petroleum waste composting

Composting is being widely employed in the treatment of petroleum waste. The purpose of this study was to find the optimum control parameters for petroleum waste in-vessel composting. Various physical and chemical parameters were monitored to evaluate their influence on the microbial communities present in composting. The CO2 evolution and the number of microorganisms were measured as the activity of composting. The results demonstrated that the optimum temperature, pH and moisture content were 56.5 - 59.5 degreesC, 7.0 - 8.5 and 55 % - 60%, respectively. Under the optimum conditions, the removal efficiency of petroleum hydrocarbon reached 83.29% after 30 days composting.

Design and optimization of photonic crystal coupling layer for bi-color quantum well infrared photodetectors

Finite difference time domain (FDTD) method is used for the simulation and analysis of electromagnetic field in the top coupling layer of GaAs/AlGaAs quantum well infrared photodetector (QWIP). Simulation results demonstrated the coupling efficiencies and distributions of electromagnetic (EM) field in a variety of 2D photonic crystal coupling layer structures. A photonic crystal structure for bi-color-QWIP is demonstrated with high coupling efficiency for two wavelengths.

Optimization of metamorphic InGaAs quantum wells on GaAs grown by molecular beam epitaxy

We investigate the molecular beam epitaxy growth of metamorphic InxGa(1-x)As materials (x up to 0.5) on GaAs substrates systematically. Optimization of structure design and growth parameters is aimed at obtaining smooth surface and high optical quality. The optimized structures have an average surface roughness of 0.9-1.8 nm. It is also proven by PL measurements that the optical properties of high indium content (55%) InGaAs quantum wells are improved apparently by defect reduction technique and by introducing Sb as a surfactant. These provide us new ways for growing device quality metamorphic structures on GaAs substrates with long-wavelength emissions.

Fabrication and optical optimization of spot-size converters with strong cladding layers

A silicon-on-insulator (SOI) optical fiber-to-waveguide spot-size converter (SSC) overlaid with specially treated silica is investigated for integrated optical circuits. Unlike the conventional process of simply depositing the hot silica on silicon waveguides, two successive layers of silicon dioxide were grown on etched SSC structures by PECVD (plasma-enhanced chemical vapor deposition). The two layers have 0.8% index contrast and supply stronger cladding for an incident light beam. Additionally, this process is able to reduce the effective refractive index of the input mode to less than 1.47 (extremely close to that of the fiber), substantially weakening the unwanted back reflection. Exploiting this technology, it was demonstrated that the SSC showed a theoretical low mode mismatch loss of 1.23 dB for a TE-like mode and has an experimental coupling efficiency of 66%.

Overall optimization of high-speed semiconductor laser modules

Based on the high frequency techniques such as frequency response measurement, equivalent circuit modeling and packaging parasitics compensation, a comprehensive optimization method for packaging high-speed semiconductor laser module is presented in this paper. The experiments show that the small-signal magnitude frequency response of the TO packaged laser module is superior to that of laser diode in frequencies, and the in-band flatness and the phase-frequency linearity are also improved significantly.

Optimization of GaInNAs(Sb)/GaAs quantum wells at 1.3-1.55 mu m grown by molecular beam epitaxy

The InGaNAs(Sb)/(GaNAs)/GaAs quantum wells (QWs) emitting at 1.3-1.55 mu m have been grown by molecular beam epitaxy (MBE). The parameters of the radio frequency (RF) such as RF power and flow rate are optimized to reduce the damages from the ions or energetic species. The growth temperature is carefully controlled to prevent the phase segregation and strain relaxation. The effects of Sb on the wavelength and quality are investigated. The GaNAs barrier is used to extend the wavelength and reduce the strain. A 1.5865 mu m InGaNAs(Sb)/GaNAs SQW edge emitting laser lasing at room temperature at continuous wave operation mode is demonstrated. (c) 2006 Elsevier B.V. All rights reserved.