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Motion Planning

11 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 2018AI-liu/Complex-YOLO

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

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

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

STRIPStream: Integrating Symbolic Planners and Blackbox Samplers

23 Feb 2018caelan/pddlstream

Many planning applications involve complex relationships defined on high-dimensional, continuous variables.

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

Egocentric Vision-based Future Vehicle Localization for Intelligent Driving Assistance Systems

19 Sep 2018MoonBlvd/tad-IROS2019-TBD-

Predicting the future location of vehicles is essential for safety-critical applications such as advanced driver assistance systems (ADAS) and autonomous driving.

AUTONOMOUS DRIVING MOTION PLANNING OPTICAL FLOW ESTIMATION

Learning Configuration Space Belief Model from Collision Checks for Motion Planning

22 Jan 2019sumitsk/cspace_belief

Our aim is to reduce the expected number of collision checks by creating a belief model of the configuration space using results from collision tests.

MOTION PLANNING