1,721,168 research outputs found
Domination between traffic matrices
Full text linkA traffic matrix D-1 dominates a traffic matrix D-2 if any capacity reservation supporting D-1 supports D-2 as well. We prove that D-1 dominates D-2 if and only if D-1, considered as a capacity reservation, supports D-2. We show several generalizations of this result
Real-Time Motion Generation for Mobile Manipulators via NMPC with Balance Constraints
No full textWe present a novel real-time motion generation approach for mobile manipulators which maintains balance even when the robot is called to execute aggressive motions. The proposed approach is based on Nonlinear Model Predictive Control (NMPC) and uses the robot full dynamics as prediction model. Robot balance is maintained by enforcing a constraint that restricts the feasible set of robot motions to those generating non-negative moments around the edges of the support polygon. This balance constraint, inherently nonlinear, is linearized using the NMPC solution of the previous iteration. In this way we facilitate the solution of the NMPC and we achieve real-time performance without compromising robot safety. We validate our approach in scenarios of increasing difficulty and compare its performance with two other methods from the literature. The simulation results show that our method can generate motions that maintain balance in challenging situations where the other techniques fail
A Dynamics-Aware NMPC Method for Robot Navigation Among Moving Obstacles
No full textWe present a novel method for mobile robot navigation among obstacles. Our approach is based on Nonlinear Model Predictive Control (NMPC) and uses a dynamics-aware collision avoidance constraint. The constraint, built upon the notion of avoidable collision state, considers not only the robot-obstacle distance but also their velocity as well as the robot actuation capabilities. To highlight the effectiveness of this constraint, we compare the proposed method with a version of the NMPC that uses a constraint purely based on distance information, showing that the first achieves better performance than the second, especially when the robot travels at higher speed among several moving obstacles. Results indicate that the method can work with relatively short prediction horizons and is therefore amenable to real-time implementation
Clique family inequalities for the stable set polytope of quasi-line graphs
No full textIn one of fundamental works in combinatorial optimization, Edmonds gave a complete linear description of the matching polytope. Matchings in a graph are equivalent to stable sets in its line graph. Also the neighborhood of any vertex in a line graph partitions into two cliques: graphs with this latter property are called quasi-line graphs. Quasi-line graphs are a subclass of claw-free graphs, and as for claw-free graphs, there exists a polynomial algorithm for finding a maximum weighted stable set in such graphs, but we do not have a complete characterization of their stable set polytope (SSP). In the paper, we introduce a class of inequalities, called clique-family inequalities, which are valid for the SSP of any graph and match the odd set inequalities defined by Edmonds for the matching polytope. This class of inequalities unifies all the known (non-trivial) facet inducing inequalities for the SSP of a quasi-line graph. We, therefore, conjecture that all the non-trivial facets of the SSP of a quasi-line graph belong to this class. We show that the conjecture is indeed correct for the subclasses of quasi-line graphs for which we have a complete description of the SSP. We discuss some approaches for solving the conjecture and a related problem. (C) 2003 Elsevier B.V. All rights reserved
Towards Safe Human-Quadrotor Interaction: Mixed-Initiative Control via Real-Time NMPC
Full text linkThis paper presents a novel algorithm for blending human inputs and automatic controller commands, guaranteeing safety in mixed-initiative interactions between humans and quadrotors. The algorithm is based on nonlinear model predictive control (NMPC) and involves using the state solution to assess whether safety- and/or task-related rules are met to mix control authority. The mixing is attained through the convex combination of human and actual robot costs and is driven by a continuous function that measures the rules' violation. To achieve real-time feasibility, we rely on an efficient real-time iteration (RTI) variant of a sequential quadratic programming (SQP) scheme to cast the mixed-initiative controller. We demonstrate the effectiveness of our algorithm through numerical simulations, where a second autonomous algorithm is used to emulate the behavior of pilots with different skill levels. Simulations show that our scheme provides suitable assistance to pilots, especially novices, in a workspace with obstacles while underpinning computational efficiency
Anti-Jackknifing Control of Tractor-Trailer Vehicles via Intrinsically Stable MPC
Full text linkIt is common knowledge that tractor-trailer vehicles are affected by jackknifing, a phenomenon that consists in the divergence of the trailer hitch angle and ultimately causes the vehicle to fold up. For the case of backwards motion, in which jackknifing can also occur at low speeds, we present a control method that drives the vehicle along a reference Cartesian trajectory while avoiding the divergence of the hitch angle. In particular, a feedback control law is obtained by combining two actions: a tracking term, computed using input-output linearization, and a corrective term, generated via IS-MPC, an intrinsically stable MPC scheme which is effective for stable inversion of nonminimum-phase systems. The proposed method has been verified in simulation and experimentally validated on a purposely built prototype
Different ways to success: Plant community trajectories over time and a soil moisture gradient in restored wetlands
Full text linkEcological restoration is one of the most promising strategies to combat historical wetland losses caused by land use changes. Restored areas are ideal sites to study plant succession and changes in ecosystem functions over time. However, little is known about the influence of restoration on plant succession along environmental stress gradients. Knowing the processes and mechanisms driving the succession over time in contrasting abiotic conditions might provide new insight into the ultimate success of an ecological restoration. Relying on long-term vegetation monitoring, we studied the community succession of 4 plant communities along a restored waterlogging gradient in North-East Italy (from high to low soil saturation level): (i) Cladium fens, (ii) low alkaline fens, (iii) Molina wet meadows and (iv) dry meadows. We monitored 23 permanent plots distributed along the gradient, spanning from 1 to 21 years since restoration, and 4 plots as target vegetation (natural habitats). We analysed the changes in plant communities in terms of functional traits, diversity and species composition. We found that exotic and annual species decreased in mature stages of restoration while leaf dry matter content increased over time. Nutrient indicator value and leaf area showed opposite trends at the extreme points of the gradient. Across the successional stages, species richness decreased in Cladium fens and increased in alkaline fens and meadows. Species composition moved toward target vegetation showing contrasting dynamics between different restored habitats. Synthesis and applications. During succession waterlogging stress acts as main abiotic filter, triggering contrasting trajectories of plant communities. This filter seems to be stronger at the extreme points of the gradient generating opposite but faster dynamics than at intermediate conditions. Time and waterlogging promoted a continuous selection of species consistent to target vegetation in terms of richness, functional traits and composition. The evidenced trajectories suggest the need to develop habitat-specific protocols concerning the selection of restoration site and subsequent management decisions, with particular regard to plant communities at intermediate ecological conditions
Image-based visual servoing for nonholonomic mobile robots using epipolar geometry
No full textWe present an image-based visual servoing strategy for driving a nonholonomic mobile robot equipped with a pinhole camera toward a desired configuration. The proposed approach, which exploits the epipolar geometry defined by the current and desired camera views, does not need any knowledge of the 3-D scene geometry. The control scheme is divided into two steps. In the first, using an approximate input–output linearizing feedback, the
epipoles are zeroed so as to align the robot with the goal. Feature
points are then used in the second translational step to reach the
desired configuration. Asymptotic convergence to the desired con-
figuration is proven, both in the calibrated and partially calibrated
case. Simulation and experimental results show the effectiveness of the proposed control scheme
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