Motion Planning

154 papers with code • 0 benchmarks • 4 datasets


Use these libraries to find Motion Planning models and implementations
3 papers

Most implemented papers

Complex-YOLO: Real-time 3D Object Detection on Point Clouds

maudzung/Complex-YOLOv4-Pytorch 16 Mar 2018

We introduce Complex-YOLO, a state of the art real-time 3D object detection network on point clouds only.

Learning Latent Dynamics for Planning from Pixels

google-research/planet 12 Nov 2018

Planning has been very successful for control tasks with known environment dynamics.

Motion Planning Among Dynamic, Decision-Making Agents with Deep Reinforcement Learning

mfe7/cadrl_ros 4 May 2018

This work extends our previous approach to develop an algorithm that learns collision avoidance among a variety of types of dynamic agents without assuming they follow any particular behavior rules.

Formation Control for Connected and Automated Vehicles on Multi-lane Roads: Relative Motion Planning and Conflict Resolution

cmc623/Multi-lane-formation-control 18 Mar 2021

Multi-vehicle coordinated decision making and control can improve traffic efficiency while guaranteeing driving safety.

STRIPS Planning in Infinite Domains

caelan/stripstream 1 Jan 2017

We introduce STRIPStream: an extension of the STRIPS language which can model these domains by supporting the specification of blackbox generators to handle complex constraints.

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning

caelan/pddlstream 23 Feb 2018

We extend PDDL to support a generic, declarative specification for these procedures that treats their implementation as black boxes.

Neural Contraction Metrics for Robust Estimation and Control: A Convex Optimization Approach

astrohiro/ncm 8 Jun 2020

This paper presents a new deep learning-based framework for robust nonlinear estimation and control using the concept of a Neural Contraction Metric (NCM).

One Thousand and One Hours: Self-driving Motion Prediction Dataset

wenkaip-1836890/pyromid_l5prediction 25 Jun 2020

Motivated by the impact of large-scale datasets on ML systems we present the largest self-driving dataset for motion prediction to date, containing over 1, 000 hours of data.

Efficient and High-quality Prehensile Rearrangement in Cluttered and Confined Spaces

rui1223/uniform_object_rearrangement 6 Oct 2021

The new monotone solver is integrated with a global planner to solve non-monotone instances with high-quality solutions fast.

Socially Aware Motion Planning with Deep Reinforcement Learning

mit-acl/gym-collision-avoidance 26 Mar 2017

For robotic vehicles to navigate safely and efficiently in pedestrian-rich environments, it is important to model subtle human behaviors and navigation rules (e. g., passing on the right).