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FineCog-Nav: Integrating Fine-grained Cognitive Modules for Zero-shot Multimodal UAV Navigation DENALI: A Dataset Enabling Non-Line-of-Sight Spatial Reasoning with Low-Cost LiDARs SENSE: Stereo OpEN Vocabulary SEmantic Segmentation Continual Hand-Eye Calibration for Open-world Robotic Manipulation PLAF: Pixel-wise Language-Aligned Feature Extraction for Efficient 3D Scene Understanding GaussianFlow SLAM: Monocular Gaussian Splatting SLAM Guided by GaussianFlow GIST: Multimodal Knowledge Extraction and Spatial Grounding via Intelligent Semantic Topology $π_{0.7}$: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities R3D: Revisiting 3D Policy Learning Vision-Based Safe Human-Robot Collaboration with Uncertainty Guarantees Benchmarking Classical Coverage Path Planning Heuristics on Irregular Hexagonal Grids for Maritime Coverage Scenarios NEAT-NC: NEAT guided Navigation Cells for Robot Path Planning HRDexDB: A Large-Scale Dataset of Dexterous Human and Robotic Hand 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Reinforcement Learning Accelerating Transformer-Based Monocular SLAM via Geometric Utility Scoring 3D-VCD: Hallucination Mitigation in 3D-LLM Embodied Agents through Visual Contrastive Decoding Action Images: End-to-End Policy Learning via Multiview Video Generation Towards Generalizable Robotic Manipulation in Dynamic Environments General-purpose LLMs as Models of Human Driver Behavior: The Case of Simplified Merging Uncertainty, Vagueness, and Ambiguity in Human-Robot Interaction: Why Conceptualization Matters IROSA: Interactive Robot Skill Adaptation using Natural Language Online Navigation Planning for Long-term Autonomous Operation of Underwater Gliders Optimized Human-Robot Co-Dispatch Planning for Petro-Site Surveillance under Varying Criticalities MerNav: A Highly Generalizable Memory-Execute-Review Framework for Zero-Shot Object Goal Navigation From Instruction to Event: Sound-Triggered Mobile Manipulation Self-Organizing Dual-Buffer Adaptive Clustering Experience Replay (SODACER) for Safe Reinforcement Learning in Optimal Control Enhanced-FQL($λ$), an Efficient and Interpretable RL with novel Fuzzy Eligibility Traces and Segmented Experience Replay LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving Learning to Plan, Planning to Learn: Adaptive Hierarchical RL-MPC for Sample-Efficient Decision Making Target-Bench: Can Video World Models Achieve Mapless Path Planning with Semantic Targets? Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis Towards Deploying VLA without Fine-Tuning: Plug-and-Play Inference-Time VLA Policy Steering via Embodied Evolutionary Diffusion Volumetric Ergodic Control RoboTAG: End-to-end Robot Configuration Estimation via Topological Alignment Graph TwinOR: Photorealistic Digital Twins of Dynamic Operating Rooms for Embodied AI Research Multimodal Diffusion Forcing for Forceful Manipulation X-Diffusion: Training Diffusion Policies on Cross-Embodiment Human Demonstrations Hierarchical DLO Routing with Reinforcement Learning and In-Context Vision-language Models Flow with the Force Field: Learning 3D Compliant Flow Matching Policies from Force and Demonstration-Guided Simulation Data AFFORD2ACT: Affordance-Guided Automatic Keypoint Selection for Generalizable and Lightweight Robotic Manipulation HAMLET: Switch your Vision-Language-Action Model into a History-Aware Policy TimeRewarder: Learning Dense Reward from Passive Videos via Frame-wise Temporal Distance Multi-Modal Manipulation via Multi-Modal Policy Consensus AutoDrive-R$^2$: Incentivizing Reasoning and Self-Reflection Capacity for VLA Model in Autonomous Driving Constrained Decoding for Safe Robot Navigation Foundation Models FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction PRIX: Learning to Plan from Raw Pixels for End-to-End Autonomous Driving LLM-based Realistic Safety-Critical Driving Video Generation Scalable Multi-Task Learning through Spiking Neural Networks with Adaptive Task-Switching Policy for Intelligent Autonomous Agents Learning to Play Piano in the Real World Scalable Unseen Objects 6-DoF Absolute Pose Estimation with Robotic Integration Sixth-Sense: Self-Supervised Learning of Spatial Awareness of Humans from a Planar Lidar Curriculum-based Sample Efficient Reinforcement Learning for Robust Stabilization of a Quadrotor Generative Models and Connected and Automated Vehicles: A Survey in Exploring the Intersection of Transportation and AI Convex Hulls of Reachable Sets
MPC path-planner for autonomous driving solved by genetic algorithm technique
Stefano Arrigoni, Francesco Braghin, Federico Cheli · 2021-02-02 · via cs.RO updates on arXiv.org

Autonomous vehicle's technology is expected to be disruptive for automotive industry in next years. This paper proposes a novel real-time trajectory planner based on a Nonlinear Model Predictive Control (NMPC) algorithm. A nonlinear single track vehicle model with Pacejka's lateral tyre formulas has been implemented. The numerical solution of the NMPC problem is obtained by means of the implementation of a novel genetic algorithm strategy. Numerical results are discussed through simulations that shown a reasonable behavior of the proposed strategy in presence of static or moving obstacles as well as in a wide rage of road friction conditions. Moreover a real-time implementation is made possible by the reported computational time analysis.

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