Motion Planning
195 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 with no code
DELTA: Decomposed Efficient Long-Term Robot Task Planning using Large Language Models
Recent advancements in Large Language Models (LLMs) have sparked a revolution across various research fields.
A Framework for Guided Motion Planning
Randomized sampling based algorithms are widely used in robot motion planning due to the problem's intractability, and are experimentally effective on a wide range of problem instances.
A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches
Task and Motion Planning (TAMP) integrates high-level task planning and low-level motion planning to equip robots with the autonomy to effectively reason over long-horizon, dynamic tasks.
QuAD: Query-based Interpretable Neural Motion Planning for Autonomous Driving
Instead, we shift the paradigm to have the planner query occupancy at relevant spatio-temporal points, restricting the computation to those regions of interest.
Efficient Motion Planning for Manipulators with Control Barrier Function-Induced Neural Controller
Our method combines the strength of CBF for real-time collision-avoidance control and RRT for long-horizon motion planning, by using CBF-induced neural controller (CBF-INC) to generate control signals that steer the system towards sampled configurations by RRT.
Accelerating Search-Based Planning for Multi-Robot Manipulation by Leveraging Online-Generated Experiences
An exciting frontier in robotic manipulation is the use of multiple arms at once.
RH20T-P: A Primitive-Level Robotic Dataset Towards Composable Generalization Agents
The ultimate goals of robotic learning is to acquire a comprehensive and generalizable robotic system capable of performing both seen skills within the training distribution and unseen skills in novel environments.
An Efficient Risk-aware Branch MPC for Automated Driving that is Robust to Uncertain Vehicle Behaviors
One of the critical challenges in automated driving is ensuring safety of automated vehicles despite the unknown behavior of the other vehicles.
Optimal Control Synthesis of Markov Decision Processes for Efficiency with Surveillance Tasks
Our objective is to synthesize a control policy that ensures the surveillance task while maximizes the efficiency.
SLEDGE: Synthesizing Simulation Environments for Driving Agents with Generative Models
SLEDGE is the first generative simulator for vehicle motion planning trained on real-world driving logs.
