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Motion Planning

22 papers with code · Robots

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Learning Latent Dynamics for Planning from Pixels

12 Nov 2018google-research/planet

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

CONTINUOUS CONTROL MOTION PLANNING

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

16 Mar 2018maudzung/Complex-YOLOv4-Pytorch

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

3D OBJECT DETECTION AUTONOMOUS DRIVING MOTION PLANNING REGION PROPOSAL

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

4 May 2018mfe7/cadrl_ros

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.

DECISION MAKING MOTION PLANNING

miniSAM: A Flexible Factor Graph Non-linear Least Squares Optimization Framework

3 Sep 2019dongjing3309/minisam

Many problems in computer vision and robotics can be phrased as non-linear least squares optimization problems represented by factor graphs, for example, simultaneous localization and mapping (SLAM), structure from motion (SfM), motion planning, and control.

MOTION PLANNING SIMULTANEOUS LOCALIZATION AND MAPPING

3D BAT: A Semi-Automatic, Web-based 3D Annotation Toolbox for Full-Surround, Multi-Modal Data Streams

1 May 2019walzimmer/3d-bat

In this paper, we focus on obtaining 2D and 3D labels, as well as track IDs for objects on the road with the help of a novel 3D Bounding Box Annotation Toolbox (3D BAT).

MOTION PLANNING MOTION PREDICTION

Motion Planning Networks: Bridging the Gap Between Learning-based and Classical Motion Planners

13 Jul 2019ahq1993/MPNet

We validate MPNet against gold-standard and state-of-the-art planning methods in a variety of problems from 2D to 7D robot configuration spaces in challenging and cluttered environments, with results showing significant and consistently stronger performance metrics, and motivating neural planning in general as a modern strategy for solving motion planning problems efficiently.

CONTINUAL LEARNING MOTION PLANNING

Deeply Informed Neural Sampling for Robot Motion Planning

26 Sep 2018ahq1993/MPNet

In this paper, we present a neural network-based adaptive sampler for motion planning called Deep Sampling-based Motion Planner (DeepSMP).

MOTION PLANNING

Motion Planning Networks

14 Jun 2018ahq1993/MPNet

Fast and efficient motion planning algorithms are crucial for many state-of-the-art robotics applications such as self-driving cars.

MOTION PLANNING SELF-DRIVING CARS TRANSFER LEARNING

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

23 Feb 2018caelan/pddlstream

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

MOTION PLANNING

STRIPS Planning in Infinite Domains

1 Jan 2017caelan/pddlstream

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.

MOTION PLANNING