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Joint Stiction Avoidance with Null-Space Motion in Real-Time Model Predictive Control for Redundant Collaborative Robots

Model Predictive Control (MPC) is an efficient point-to-point trajectory-generation method for robots that can be used in situations that occur under time constraints. The motion plan can be recalculated online to increase the accuracy of the trajectory when getting close to the goal position. We have implemented this strategy in a Franka Emika Panda robot, a redundant collaborative robot, by exte

The power of negative reasoning

Semialgebraic proof systems have been studied extensively in proof complexity since the late 1990s to understand the power of Gröbner basis computations, linear and semidefinite programming hierarchies, and other methods. Such proof systems are defined alternately with only the original variables of the problem and with special formal variables for positive and negative literals, but there seems t

Safe and Robust Autonomous Intersection Management Methods

Connected Autonomous Vehicles (AV)s can transform urban transportation systems and have the potential to improve the safety and efficiency, since human errors and distractions are removed. However, these systems are vulnerable to model uncertainties, communication impairments associated with the wireless communication, and external disturbances. As a result, vehicles need to drive at low speed and

On the Tightness of Semidefinite Relaxations for Rotation Estimation

Why is it that semidefinite relaxations have been so successful in numerous applications in computer vision and robotics for solving non-convex optimization problems involving rotations? In studying the empirical performance, we note that there are few failure cases reported in the literature, in particular for estimation problems with a single rotation, motivating us to gain further theoretical u

The boreal-arctic wetland and lake dataset (BAWLD)

Methane emissions from boreal and arctic wetlands, lakes, and rivers are expected to increase in response to warming and associated permafrost thaw. However, the lack of appropriate land cover datasets for scaling field-measured methane emissions to circumpolar scales has contributed to a large uncertainty for our understanding of present-day and future methane emissions. Here we present the Borea

Inverse optimal control for angle stabilization in converter-based generation

In inverse optimal control, an optimal controller is synthesized with respect to a meaningful, a posteriori defined, cost functional. Our work illustrates the usefulness of this approach in the control of converter-based power systems and networked systems in general, and thereby in finding controllers with topological structure and known optimality properties. In particular, we design an inverse

Efficient Proximal Mapping Computation for Low-Rank Inducing Norms

Low-rank inducing unitarily invariant norms have been introduced to convexify problems with a low-rank/sparsity constraint. The most well-known member of this family is the so-called nuclear norm. To solve optimization problems involving such norms with proximal splitting methods, efficient ways of evaluating the proximal mapping of the low-rank inducing norms are needed. This is known for the nuc

Network Modeling and Performance Evaluation for G.fast

G.fast is a gap-bridging broadband technology on the way to a fully optical access network. G.fast is deployed in hybrid fiber-copper access networks and aiming to offer ubiquitous low-cost and high-speed broadband. For network operators, it is crucial to determine the location from where to deploy G.fast, the expected network coverage, and the expected bit rates. In this paper, we perform network

A Virtualized LoRa Testbed and Experimental Results for Resource Pooling

Traditional network architecture design of Low Power Wide Area Networks (LPWAN) is incapable of dynamically scaling resources based on the served traffic and requires manual procedures for network capacity upgrades. Today's over-provisioning approach based on proprietary hardware (HW) would not be cost and energy efficient to cope with the ever-increasing scale of Internet of Things (IoT) devices

Real-Time Rendering of Indirectly Visible Caustics

Caustics are a challenging light transport phenomenon to render in real-time, and most previous approaches have used screen-space accumulation based on the fast rasterization hardware of GPUs. This limits the position of photon collection points to first hit screen space locations, and leads to missing caustics that should be visible in a mirror’s reflection. In this paper we propose an algorithm

Clique Is Hard on Average for Regular Resolution

We prove that for k ≫; 4√n regular resolution requires length nω(k) to establish that an ErdÅ's-Rényi graph with appropriately chosen edge density does not contain a k-clique. This lower bound is optimal up to the multiplicative constant in the exponent and also implies unconditional nω(k) lower bounds on running time for several state-of-the-art algorithms for finding maximum cliques in graphs.

The AIQ Meta-Testbed : Pragmatically Bridging Academic AI Testing and Industrial Q Needs

AI solutions seem to appear in any and all application domains. As AI becomes more pervasive, the importance of quality assurance increases. Unfortunately, there is no consensus on what artificial intelligence means and interpretations range from simple statistical analysis to sentient humanoid robots. On top of that, quality is a notoriously hard concept to pinpoint. What does this mean for AI qu

Development of boosted machine learning models for estimating daily reference evapotranspiration and comparison with empirical approaches

Proper irrigation scheduling and agricultural water management require a precise estimation of crop water requirement. In practice, reference evapotranspiration (ETo) is firstly estimated, and used further to calculate the evapotranspiration of each crop. In this study, two new coupled models were developed for estimating daily ETo. Two optimization algorithms, the shuffled frog-leaping algorithm

Finite-size scaling analysis of protein droplet formation

The formation of biomolecular condensates inside cells often involve intrinsically disordered proteins (IDPs), and several of these IDPs are also capable of forming dropletlike dense assemblies on their own, through liquid-liquid phase separation. When modeling thermodynamic phase changes, it is well known that finite-size scaling analysis can be a valuable tool. However, to our knowledge, this ap

Investigating the role of the tibetan plateau in ENSO variability

The role of the Tibetan Plateau (TP) in El Niño-Southern Oscillation (ENSO) variability is investigated using coupled model experiments with different topography setups. Removing the TP results in weakened trade winds in the tropical Pacific, an eastward shift of atmospheric convection center, a shallower mixed layer in the equatorial Pacific, and a flattened equatorial thermocline, which leads to

EpilepsyGAN : Synthetic Epileptic Brain Activities with Privacy Preservation

Epilepsy is a chronic neurological disorder affecting more than 65 million people worldwide and manifested by recurrent unprovoked seizures. The unpredictability of seizures not only degrades the quality of life of the patients, but it can also be life-threatening. Modern systems monitoring elec-troencephalography (EEG) signals are being currently developed with the view to detect epileptic seizur

A Micro-Simulation Study of the Generalized Proportional Allocation Traffic Signal Control

We study the problem of controlling phase activations for signalized junctions in an urban transportation network using local feedback information consisting of measures of the queue-lengths at the incoming lanes of each junction. Our focus is on the validation and performance evaluation through micro-simulations of the recently proposed Generalized Proportional Allocation (GPA) controller. Previo

Response of heterogeneous rainfall variability in East Asia to Hadley circulation reorganization during the late Quaternary

The Quaternary East Asian summer rainfall evolution reconstructed with the Chinese speleothem δ18O records shows the consistency throughout the region of East Asia, and has long been considered equivalent to the monsoon intensity. Its variation and teleconnection with global climate were usually interpreted by the meridional shift of the intertropical convergence zone (ITCZ). However, many other p