Shuijing725/CrowdNav_Prediction_AttnGraph
[ICRA 2023] Intention Aware Robot Crowd Navigation with Attention-Based Interaction Graph
This project helps robots navigate safely and smoothly through dense crowds by predicting where people are heading. It takes in real-time sensor data about the crowd and outputs optimized robot movement commands, allowing the robot to avoid collisions and respect personal space. This is ideal for robotics engineers and autonomous system developers creating robots for public spaces like airports, malls, or warehouses.
242 stars. No commits in the last 6 months.
Use this if you need to deploy an autonomous robot in environments with many moving people and want it to navigate proactively and non-invasively.
Not ideal if your robot operates in static environments, sparse crowds, or where human interaction is not a primary concern.
Stars
242
Forks
46
Language
Python
License
MIT
Category
Last pushed
Dec 10, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Shuijing725/CrowdNav_Prediction_AttnGraph"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
StanfordASL/Trajectron
Code accompanying "The Trajectron: Probabilistic Multi-Agent Trajectory Modeling with Dynamic...
StanfordASL/Trajectron-plus-plus
Code accompanying the ECCV 2020 paper "Trajectron++: Dynamically-Feasible Trajectory Forecasting...
agrimgupta92/sgan
Code for "Social GAN: Socially Acceptable Trajectories with Generative Adversarial Networks",...
uber-research/LaneGCN
[ECCV2020 Oral] Learning Lane Graph Representations for Motion Forecasting
Psychic-DL/Awesome-Traffic-Agent-Trajectory-Prediction
This is a list of papers related to traffic agent trajectory prediction.