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p2o

Single header 2D/3D graph-based SLAM library

panda_simulation

Package for the dynamic simulation of the Franka Emika Panda robot arm in Gazebo

particlesolver

CPU and GPU implementations of a particle-based physics simulation based on Macklin et. al's "Unified Particle Physics for Real-Time Application".

path_optimizer

Real-time path planning for non-holonomic vehicles.

path_planner

Hybrid A* Path Planner for the KTH Research Concept Vehicle

path_planning

This repository contains path planning algorithms in C++ for a grid based search.

pathplanning

Common used path planning algorithms with animations.

pddl-parser

:snake: Classical Planning in Python

pddlgym

Convert a PDDL domain into an OpenAI Gym environment.

pddlstream

PDDLStream: Integrating Symbolic Planners and Blackbox Samplers

phyre-reasoning-about-paths

Solving Physics Puzzles by Reasoning about Paths (NeurIPS 2020 workshop)

pick-place-robot

Object picking and stowing with a 6-DOF KUKA Robot using ROS

plasp

🗺️ ASP planning tools for PDDL

plotjuggler

The Time Series Visualization Tool that you deserve.

point-cloud-simulator

point-cloud-simulator-1

This is a LiDAR point cloud processing software. It has features to add synthetic noise to a given point cloud, remove noise and detect objects.

point_cloud_transport_tutorial

This repository provides tutorial, which discusses running sample publisher and subscriber using multiple transports of point_cloud_transport.

pose-estimation

Easy to use SOTA Top-Down Multi-person Pose Estimation Models in PyTorch

poselib

Minimal solvers for calibrated camera pose estimation

prasemap

A Probability Reasoning and Semantic Embedding-based Knowledge Graph Alignment System

prepare_detection_dataset

convert dataset to coco/voc format

prm_planner

The probabilistic roadmap (PRM) planner uses a graph of task poses to find a path between the start and goal poses.

problog

ProbLog is a Probabilistic Logic Programming Language for logic programs with probabilities.

probqa

Probabilistic question-asking system: the program asks, the users answer. The minimal goal of the program is to identify what the user needs (a target), even if the user is not aware of the existence of such thing/product/service. The maximal goal is to achieve the processing power of a single neuron of a human brain on a single PC. Interactions with billions of other computers should achieve human-level intelligence (AGI).

prolog_bfs

A simple implementation of a breadth first search prolog interpreter

prologcoin

prost

probabilistic planning system for tasks encoded in RDDL

pybullet-planning

PyBullet Planning

pycubicspline

Cubic spline library on python

pyddl

STRIPS planner with PDDL-like problem specification in Python