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Deep Latent Competition: Learning to Race Using Visual Control Policies in Latent Space

Learning competitive behaviors in multi-agent settings such as racing requires long-term reasoning about potential adversarial interactions. This paper presents Deep Latent Competition (DLC), a novel reinforcement learning algorithm that learns …

Differentiable Logic Layer for Rule Guided Trajectory Prediction

Exploiting Semantic and Public Prior Information in MonoSLAM

In this paper, we propose a method to use semantic information to improve the use of map priors in a sparse, feature-based MonoSLAM system. To incorporate the priors, the features in the prior and SLAM maps must be associated with one another. Most …

Deep Orientation Uncertainty Learning based on a Bingham Loss

Reasoning about uncertain orientations is one of the core problems in many perception tasks such as object pose estimation or motion estimation. In these scenarios, poor illumination conditions, sensor limitations, or appearance invariance may result …

Infrastructure-free NLoS Obstacle Detection for Autonomous Cars

Current perception systems mostly require direct line of sight to anticipate and ultimately prevent potential collisions at intersections with other road users. We present a fully integrated autonomous system capable of detecting shadows or weak …

Range-based Cooperative Localization with Nonlinear Observability Analysis

Accurate localization of other cars in scenarios such as intersection navigation, intention-aware planning, and guardian systems is a critical component of safety. Multi-robot cooperative localization (CL) provides a method to estimate the joint …

Data-Dependent Coresets for Compressing Neural Networks with Applications to Generalization Bounds

We present an efficient coresets-based neural network compression algorithm that sparsifies the parameters of a trained fully-connected neural network in a manner that provably approximates the network's output. Our approach is based on an importance …

ShadowCam: Real-Time Detection of Moving Obstacles behind a Corner for Autonomous Vehicles

Moving obstacles occluded by corners are a poten- tial source for collisions in mobile robotics applications such as autonomous vehicles. In this paper, we address the problem of anticipating such collisions by proposing a vision-based detection …

LandmarkBoost: Efficient Visual Context Classifiers for Robust Localization

Map Management for Efficient Long-Term Visual Localization in Outdoor Environments

We present a complete map management process for a visual localization system designed for multi-vehicle longterm operations in resource constrained outdoor environments. Outdoor visual localization generates large amounts of data that need to be …