Residual neural networks improve collision prediction in planetary simulations.
problem Accurate prediction of planetary collisions in N-body simulations.
method Residual neural networks trained on collision data.
result Residual neural networks outperform existing methods in prediction accuracy and generalization.
Machine learning competition predicts spacecraft collision risks.
problem Predicting future collision risks between orbiting satellites.
method Machine learning models trained on satellite collision data.
result Models accurately predicted collision risks with high precision.
Bayesian deep learning predicts satellite collisions.
problem Space debris poses planetary risk.
method Bayesian deep learning with LSTM networks.
result Predicts conjunction event evolution with uncertainties.
SafeCritic predicts safe trajectories for pedestrians and cyclists avoiding collisions.
problem Predicting safe trajectories for pedestrians and cyclists in urban environments.
method Generative adversarial networks and reinforcement learning to generate safe trajectories, evaluated by a Discriminator.
result Significant improvement over state-of-the-art models in safety classification.
An important application of intelligent vehicles is advance detection of dangerous events such as collisions. This problem is framed as a problem of optimal alarm choice given predictive models for vehicle location and motion. Techniques for real-time collision detection are surveyed and grouped into three classes: ran…
Study shows how transformers classify symbols without naming them, proving a margin-versus-collision criterion.
problem How transformers classify symbols without naming them.
method Logistic classification analysis of transformer-kernel regime, colored collision graph.
result Decomposes learned predictor into ideal template-level classifier and finite-sample perturbation.
This study uses reinforcement learning to mitigate imminent collisions by controlling car speed and direction.
problem Mitigating imminent collisions on roads.
method Constructed a model using camera images to predict obstacle dynamics. Trained reinforcement learning policies to control braking and steering.
result Both reinforcement learning policies outperform a baseline policy, with the injury model-based policy showing the highest performance.
Study nonholonomic systems with collisions using variational principles.
problem Variational problems on nonholonomic systems with collisions.
method Extended variational principle, introduced connection on principal bundles, applied Lagrange–Poincaré–Pontryagin reduction.
result Implicit Lagrange–d'Alembert–Pontryagin equations for nonholonomic systems with collisions.
Paper analyzes dynamics of nonholonomic systems with collisions using variational techniques.
problem Analyzing the dynamics of nonholonomic mechanical systems with impacts.
method Variational techniques extended to nonsmooth context for collisions.
result Variational formulation for implicit nonholonomic mechanical systems with energy-momentum preserving collisions.
Model forecasts motor vehicle collision rates with high accuracy.
problem Forecasting motor vehicle collision rates with high accuracy.
method Adopted Heston Stochastic Volatility model and extended it to account for seasonality and accelerated safety periods.
result Short-term forecasts show high accuracy (over 95%) and outperform existing models.
Stochastic approach improves neural network training for kinetic simulations.
problem Training neural networks under physical constraints in kinetic fusion simulations.
method Stochastic augmented Lagrangian approach using pyTorch.
result Higher model prediction accuracy achieved compared to fixed penalty method.
New algorithms estimate and test collision probability with near-optimal sample complexity.
problem Estimating and testing collision probability in discrete distributions.
method Developed algorithms for ( α , β ) (α, β) ( α , β ) -local differential privacy and sequential testing. result Achieved nearly optimal sample complexity for estimating and testing collision probability.
Model predicts road vehicle accidents with high resolution.
problem Accidents on roads in Montreal.
method Big data analytics, machine learning (Balanced Random Forest algorithm).
result 85% of road vehicle collisions detected with 13% false positives.
One approach to designing decision making logic for an aircraft collision avoidance system frames the problem as a Markov decision process and optimizes the system using dynamic programming. The resulting collision avoidance strategy can be represented as a numeric table. This methodology has been used in the developme…
No-collision maps improve manifold learning for image data.
problem Lack of geometric feature sensitivity in traditional distance measures.
method Developed no-collision transportation maps and distances.
result No-collision distances provide isometry for translations and dilations.
A new metric for uncertainty quantification using class collisions.
problem Fine-grained uncertainty quantification in classification problems.
method Introducing the collision matrix and estimating it from one-hot labeled data.
result The collision matrix uniquely recovers the posterior class probability distribution.
Reduces necessary conditions for collision avoidance on curved spaces.
problem Finding non-intersecting trajectories for multiple agents on curved spaces.
method Reduction by Lie group symmetries of variational collision avoidance problems.
result Derives necessary conditions for reduced extremals.
New algorithm for multi-player bandits with collision-dependent rewards.
problem Stochastic multi-player multi-armed bandits with collision-dependent reward distributions.
method Error-Correction Collision Communication (EC3) algorithm.
result EC3 algorithm achieves optimal regret approaching centralized MP-MAB regret.
Robust collision prediction for robots using generative uncertainty.
problem Robots need to predict collisions safely in unexpected situations.
method Combines generative modeling and model uncertainty to handle out-of-distribution inputs.
result Improves collision prediction performance, especially for out-of-distribution inputs.
Algorithm reduces regret in multi-player bandits with unknown collision rewards.
problem Reducing regret in multi-player multi-armed bandits with unknown collision rewards.
method Proposes an algorithm that combines a modified successive elimination strategy with a communication protocol to estimate suboptimality gaps and coordinate among players.
result Achieves logarithmic regret for the problem when collision reward is unknown.
New algorithm reduces regret in multi-player bandits with collision information.
problem Optimizing decisions in multi-player bandits with collision penalties.
method Developed an algorithm with optimal T \sqrt{T} T regret under collision announcements, and sublinear regret without collision info. result First T \sqrt{T} T -type regret guarantee for non-stochastic multi-player multi-armed bandits with collision information. This work improves motion planning for quadcopters by learning and reasoning about controller performance.
problem Improving motion planning for quadcopters with safety margins and execution reliability.
method Introspective learning and reasoning to correct execution bias and improve collision checking.
result Substantial reduction in safety margins for motion actions, leading to safer execution.
A new algorithm reduces regret in multi-player bandits without collision info.
problem Decentralized multi-player multi-armed bandits with no collision info.
method EC-SIC algorithm using optimal error correction coding for reward statistics.
result Regret approaches that of centralized with collision info.
A new algorithm RESYNC for defenders against malicious attackers in multi-player bandits.
problem Malicious players colliding with cooperative players to prevent rewards.
method Decentralized and robust algorithm RESYNC for defenders.
result RESYNC algorithm is order-optimal, performing gracefully as the number of collisions increases.
Examining orbits ending in binary collisions for three equal masses under an inverse cube force.
problem Analyzing orbits ending in binary collisions for three equal masses under an inverse cube force.
method Reparametrizing orbits as geodesics on a negatively curved metric on a pair of pants.
result Visibility properties of negatively curved surfaces describe orbits beginning or ending in binary collisions.
A new algorithm reduces regret in multiplayer bandits with minimal communication.
problem Maximizing rewards in multiplayer multi-armed bandits with collisions.
method DPE (Decentralized Parsimonious Exploration) algorithm.
result Achieves the same regret as optimal centralized algorithms with less communication.
Due to the lack of information such as the space environment condition and resident space objects' (RSOs') body characteristics, current orbit predictions that are solely grounded on physics-based models may fail to achieve required accuracy for collision avoidance and have led to satellite collisions already. This pap…
New algorithms tackle adversarial multi-player bandits with forced-collision communication.
problem No-sensing adversarial multi-player multi-armed bandits (MP-MAB) problem.
method Adversary-Adaptive Collision-Communication (A2C2) algorithms, attackability-aware and unaware settings, information-theoretic tools, error-correction coding.
result Asymptotic attackability-dependent sublinear regret achieved, with or without knowing attackability.
New strategy achieves optimal regret without communication or collisions in multi-player bandit.
problem Cooperative multi-player stochastic multi-armed bandit with shared randomness.
method Combination of combinatorial approach to generalize geometric intuition.
result Achieves near-optimal regret i l d e O ( T ) ilde{O}(\sqrt{T}) i l d e O ( T ) for any number of players and arms without collisions. Novel method decomposes configuration space for improved collision checking.
problem Improving collision checking in high-degree-of-freedom robot motion planning.
method Proposes a configuration space decomposition method to build a composite classifier.
result Composite classifier outperforms state-of-the-art single classifier methods.
We study multiplayer stochastic multi-armed bandit problems in which the players cannot communicate and if two or more players pull the same arm, a collision occurs and the involved players receive zero reward. We consider two feedback models: a model in which the players can observe whether a collision has occurred an…
The configuration manifold M M M of a mechanical system consisting of two unconstrained rigid bodies in R n \mathbb{R}^n R n , n ≥ 1 n\geq 1 n ≥ 1 , is a manifold with boundary (typically with singularities.) A complete description of the system requires boundary conditions that specify how orbits should be continued after collisions. A b…
Study motion planning for points avoiding obstacles in a plane.
problem Avoiding collisions for multiple points in a plane with unknown obstacles.
method Algebraic and topological tools for motion planning.
result New topological complexity for planar motion planning.
Centrality, as a geometrical property of the collision, is crucial for the physical interpretation of nucleus-nucleus and proton-nucleus experimental data. However, it cannot be directly accessed in event-by-event data analysis. Common methods for centrality estimation in A-A and p-A collisions usually rely on a single…
Recovering manifold geometry from geodesic intersections.
problem Recovering the geometry of a Riemannian manifold from geodesic intersection lengths.
method Applying stitching data to solve the delayed collision data problem.
result Geometry of the manifold can be recovered from geodesic intersection lengths.
Bayesian RNNs improve safety in RL tasks.
problem Lack of explainability and safety in RL algorithms.
method Fully Bayesian Recurrent Neural Networks (RNNs) with uncertainty estimates.
result Significantly outperforms existing methods in collision avoidance tasks.
Zero-energy orbits in the Kepler-Heisenberg problem are self-similar and stratify into three families.
problem Determining the motion of a planet around a sun in the Heisenberg group.
method Analysis of the sub-Riemannian Hamiltonian and sub-Laplacian dynamics.
result Zero-energy orbits are self-similar and stratify into future collision, past collision, and quasi-periodic families.
New algorithm for multi-player bandits without needing lower bounds or scaling inversely.
problem Multi-player bandits without collision sensing information.
method Proposes a novel algorithm that circumvents two problems of existing algorithms.
result Proves a theoretical regret upper bound and shows superior performance in practice.
CMTS synthesizes near-miss driving scenarios for safer autonomous driving tests.
problem Lack of near-miss driving data for testing autonomous driving algorithms.
method Generative model conditioned on road maps, using Variational Bayesian methods.
result Synthesized data covers more near-miss scenarios, improving trajectory prediction and risk handling.
A policy for near-optimal multi-player bandits with non-zero collision rewards.
problem Decentralized multi-player bandits with heterogeneous rewards and collisions.
method A policy achieving near-optimal regret in a non-communicative setting.
result Near order-optimal expected regret of O ( log 1 + δ T ) O(\log^{1 + δ} T) O ( log 1 + δ T ) for 0 < δ < 1 0 < δ< 1 0 < δ < 1 . Unified approach detects traffic conflicts across various interactions.
problem Inconsistent detection of traffic conflicts across different interactions.
method Unified probabilistic approach decomposes conflicts into statistical learning tasks.
result Effective collision warnings across diverse datasets and environments.
Rolling systems limit to billiard models with no-slip collisions.
problem Understanding how rolling systems behave as billiard models with no-slip collisions.
method Showed that no-slip billiards arise as limits of non-holonomic rolling systems.
result Rolling systems limit to billiard models with no-slip collisions.
IC-Network improves CNNs by integrating elastic collision units.
problem Designing more effective basic units in neural networks.
method Developed IC layer and IC block units combining the IC structure with convolution operations.
result Significant performance improvements in existing CNNs, reducing top-1 error from 22.85% to 21.49% on imagenet.
New algorithm tackles multiplayer bandits with varying arm means, achieving optimal regret.
problem Stochastic multi-armed bandit problem with non-communicating players and collisions.
method Combines forced collisions for implicit communication and matching eliminations.
result First sublinear minimax regret bound of O ( ln ( T ) ) O(\ln(T)) O ( ln ( T )) for unique optimal assignment. Multipeakons are special solutions to the Camassa-Holm equation described by an integrable geodesic flow on a Riemannian manifold. We present a bi-Hamiltonian formulation of the system explicitly and write down formulae for the associated first integrals. Then we exploit the first integrals and present a novel approach…
Generalizes Landau-Ginzburg mirrors for Frobenius manifolds in Dynkin type A.
problem Classifying Frobenius manifold structures in Dynkin type A.
method Generalizing the method from previous works, developing a pole-collision framework.
result Structural result at the level of prepotential for arbitrary rank and dimension.
This paper tackles collision avoidance for many UAVs using MFG and ML.
problem Collision avoidance for many UAVs in real-time missions.
method Mean-field game (MFG) theory combined with machine learning (ML) to reduce computation and communication energy.
result The proposed MFG learning control method achieves collision avoidance with low communication and acceptable computation energy.
Models for predicting aircraft motion are an important component of modern aeronautical systems. These models help aircraft plan collision avoidance maneuvers and help conduct offline performance and safety analyses. In this article, we develop a method for learning a probabilistic generative model of aircraft motion i…