Development of a New Intelligent Algorithm to Improve Autonomous Car Operation
Autonomous Driving Systems (ADS) are transforming modern transportation by enabling safer, more efficient vehicle operation.
Engineering 5.5 · Research 8.0 · Business 5.5
Path Planning - Autonomous Driving Papers, Code and Research Roadmap
Path planning and motion planning for autonomous vehicles — route planning, trajectory optimization, decision-making and planning in complex urban traffic.
FactorDrive: Adaptive Multi-Step Reasoning Driven by Planning-Critical Factors for End-to-End Autonomous Driving
To address these limitations, we propose FactorDrive, an end-to-end autonomous driving framework for adaptive multi-step reasoning driven by planning-critical factors (PCFs).
Engineering 6.0 · Research 8.0 · Business 5.0
A Comprehensive Comparative Study of State-of-the-Art Path-Planning Algorithms for Autonomous Robots
The problem of path planning is one of the most crucial and challenging issues in the fields of intelligent systems and autonomous robotics.
Engineering 5.0 · Research 8.0 · Business 5.0
SUV: Future Scene Understanding as Video Generation for End-to-End Driving
We introduce SUV, a unified end-to-end driving framework that casts future Scene Understanding as Video generation using a pretrained video foundation model.
Engineering 5.5 · Research 8.5 · Business 5.0
PRISM: Privileged Probabilistic Latent Supervision for End-to-End Autonomous Driving Motion Planning
Building on this insight, we propose a probabilistic deep supervision framework that regularizes intermediate latent representations directly from GT data.
Engineering 6.0 · Research 7.0 · Business 5.0
Understanding the Markov decision process for reinforcement learning in robotics perception
This paper presents a formal framework and comprehensive introduction of the Markov Decision Process (MDP), together with the description of value functions and policies.
Engineering 5.0 · Research 7.0 · Business 5.0
Risk-Aware Motion Planning with Learned Trajectory Primitives and Probabilistic Safety Assessment
This paper presents a radial basis function network (RBFN)-informed motion planning framework for safe and efficient urban autonomous driving.
Engineering 5.0 · Research 7.0 · Business 5.0
Dual-layer formation control strategy for connected and mixed traffic flow utilizing fish swarm algorithm
Current research indicates that collaborative decision-making and control across several vehicles can markedly enhance traffic efficiency and driving safety.
Engineering 5.0 · Research 7.0 · Business 5.0
IntelliFly: Multi-UAV Cooperative Path Optimization for IoT-enabled Energy-efficient Smart Agriculture
An autonomous driving research paper: IntelliFly: Multi-UAV Cooperative Path Optimization for IoT-enabled Energy-efficient Smart Agriculture.
Engineering 5.0 · Research 7.0 · Business 5.0
Trajectory planning for autonomous driving on urban curvy roads: A search-resampling-enhanced iterative optimization framework
To address this issue, A Search-Resampling-Enhanced Iterative Optimization (SREIO) framework is proposed in this paper.
Engineering 5.0 · Research 8.0 · Business 5.0
Autonomous driving system for single hydrostatic transmission crawler tractor based on multi-modal steering control
Introduction Autonomous navigation of crawler tractors is essential for precision agriculture; however, existing systems often face a trade-off between path-tracking accuracy and steering stability, particularly under complex field conditions.
Engineering 5.0 · Research 7.0 · Business 5.0
HGeo-TopoMap: Boosting Topological Mapping with Hierarchical Geometric Priors
To tackle this problem, we propose HGeo-TopoMap, which leverages an explicit prior map and implicit spatial relations to hierarchically boost topological mapping.
Engineering 7.0 · Research 7.0 · Business 5.5
DVFA-RRT*: A Progress-Driven Hybrid Sampling Approach for 3D Trajectory Planning and Obstacle Avoidance
An autonomous driving research paper: DVFA-RRT*: A Progress-Driven Hybrid Sampling Approach for 3D Trajectory Planning and Obstacle Avoidance.
Engineering 5.0 · Research 7.0 · Business 5.0
Application of Multimodal Fusion Based on Sensors and Machine Vision in Autonomous Driving
Autonomous driving has become a transformative technology poised to reshape modern transportation systems.
Engineering 5.5 · Research 7.0 · Business 5.0
Safety-Aware Event-Triggered Intervention for Motion Planning and Decision Making in Diffusion-Based Autonomous Driving
Diffusion-based trajectory planners achieve strong nominal performance in autonomous driving, but sparse safety intervention remains difficult to evaluate and realize effectively.
Engineering 5.0 · Research 7.0 · Business 5.0
GeoWorldAD: Geometry World Action Model for Autonomous Driving
In this work, we propose GeoWorldAD, a geometry world action model that grounds trajectory planning in ego-aligned 3D space and anticipates short-horizon scene evolution with latent future geometry tokens.
Engineering 5.0 · Research 8.0 · Business 5.0
Task-Space Constrained Stochastic Trajectory Optimization for Time-Optimal Forestry Crane Motion Planning
This paper presents TSC-VP-STO, a task-space-constrained extension of VP-STO that replaces the strict terminal joint-space constraint with a task-space constraint, jointly optimizing the trajectory and the redundant degrees of freedom of the terminal configuration.
Engineering 5.5 · Research 7.0 · Business 6.5
DRIFT: Drift and Aggregation for Motion Planning
We present DRIFT, a fixed-depth planner that combines one-step drifting in a compact trajectory latent space with scene-aware proposal aggregation.
Engineering 5.5 · Research 7.0 · Business 5.0
S-squared-VLA: Decoupling Semantic and Spatial Streams in Vision-Language-Action Models for Autonomous Driving
To address this limitation, we propose the S-squared-VLA, which explicitly decouples the semantic and spatial streams in Vision-Language-Action models.
Engineering 5.0 · Research 8.0 · Business 5.0
A Hybrid Sampling-Based Trajectory Planner with Game-Theoretic Guidance for Autonomous Racing
This paper proposes a hybrid architecture that integrates game-theoretic reasoning into a sampling-based motion planner, combining strategic interactions with robust trajectory generation.
Engineering 5.0 · Research 7.0 · Business 5.0