Motion Planning
196 papers with code • 1 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Motion Planning
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Libraries
Use these libraries to find Motion Planning models and implementations
nuScenes
HouseExpo
ThreeDWorld Transport Challenge
PushWorld
Latest papers
DriveMLM: Aligning Multi-Modal Large Language Models with Behavioral Planning States for Autonomous Driving
In this work, we delve into the potential of large language models (LLMs) in autonomous driving (AD).
A Language Agent for Autonomous Driving
Our approach, termed Agent-Driver, transforms the traditional autonomous driving pipeline by introducing a versatile tool library accessible via function calls, a cognitive memory of common sense and experiential knowledge for decision-making, and a reasoning engine capable of chain-of-thought reasoning, task planning, motion planning, and self-reflection.
Interactive Motion Planning for Autonomous Vehicles via Adaptive Interactive MPC
The ego vehicle solves a joint optimization problem for its motion planning involving costs and coupled constraints of both vehicles and applies its own actions.
Large Trajectory Models are Scalable Motion Predictors and Planners
tsinghua-mars-lab/statetransformer
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STR reformulates the motion prediction and motion planning problems by arranging observations, states, and actions into one unified sequence modeling task.
Neural Potential Field for Obstacle-Aware Local Motion Planning
Experiment on Husky UGV mobile robot showed that our approach allows real-time and safe local planning.
GPT-Driver: Learning to Drive with GPT
In this paper, we propose a novel approach to motion planning that capitalizes on the strong reasoning capabilities and generalization potential inherent to Large Language Models (LLMs).
Perception-and-Energy-aware Motion Planning for UAV using Learning-based Model under Heteroscedastic Uncertainty
Global navigation satellite systems (GNSS) denied environments/conditions require unmanned aerial vehicles (UAVs) to energy-efficiently and reliably fly.
Multi-Agent Reach-Avoid Games: Two Attackers Versus One Defender and Mixed Integer Programming
Utilizing this result and previous results for the 1 vs. 1 game, we further propose solving the general multi-agent reach-avoid game by determining the defender assignments that can maximize the number of attackers captured via a Mixed Integer Program (MIP).
EDMP: Ensemble-of-costs-guided Diffusion for Motion Planning
vishal-2000/EDMP
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However, without a prior understanding of what diverse valid trajectories are and without specially designed cost functions for a given scene, the overall solutions tend to have low success rates.
A Novel Deep Neural Network for Trajectory Prediction in Automated Vehicles Using Velocity Vector Field
Anticipating the motion of other road users is crucial for automated driving systems (ADS), as it enables safe and informed downstream decision-making and motion planning.
