Motion Planning
193 papers with code • 1 benchmarks • 5 datasets
Libraries
Use these libraries to find Motion Planning models and implementationsLatest papers
Temporal and Semantic Evaluation Metrics for Foundation Models in Post-Hoc Analysis of Robotic Sub-tasks
To rigorously evaluate the quality of our automatic labeling framework, we contribute an algorithm SIMILARITY to produce two novel metrics, temporal similarity and semantic similarity.
LLM3:Large Language Model-based Task and Motion Planning with Motion Failure Reasoning
Through a series of simulations in a box-packing domain, we quantitatively demonstrate the effectiveness of LLM^3 in solving TAMP problems and the efficiency in selecting action parameters.
Diffusion-Reinforcement Learning Hierarchical Motion Planning in Adversarial Multi-agent Games
Reinforcement Learning- (RL-)based motion planning has recently shown the potential to outperform traditional approaches from autonomous navigation to robot manipulation.
On the Road to Portability: Compressing End-to-End Motion Planner for Autonomous Driving
However, the oversized neural networks render them impractical for deployment on resource-constrained systems, which unavoidably requires more computational time and resources during reference. To handle this, knowledge distillation offers a promising approach that compresses models by enabling a smaller student model to learn from a larger teacher model.
Learning Inverse Kinodynamics for Autonomous Vehicle Drifting
In this work, we explore a data-driven learning-based approach to learning the kinodynamic model of a small autonomous vehicle, and observe the effect it has on motion planning, specifically autonomous drifting.
Conformalized Adaptive Forecasting of Heterogeneous Trajectories
This paper presents a new conformal method for generating simultaneous forecasting bands guaranteed to cover the entire path of a new random trajectory with sufficiently high probability.
Visualizing High-Dimensional Configuration Spaces For Robots: A Comprehensive Approach for Quantitative and Qualitative Analysis
In particular, a collision checker may exhibit high accuracy even when only a subset of the original CS is reconstructed, limiting the motion planner's ability to find paths comparable to those in the original CS.
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.