Graph Policy Gradients for Large Scale Unlabeled Motion Planning with Constraints

by   Arbaaz Khan, et al.

In this paper, we present a learning method to solve the unlabelled motion problem with motion constraints and space constraints in 2D space for a large number of robots. To solve the problem of arbitrary dynamics and constraints we propose formulating the problem as a multi-agent problem. In contrast to previous works that propose using learning solutions for unlabelled motion planning with constraints, we are able to demonstrate the scalability of our methods for a large number of robots. The curse of dimensionality one encounters when working with a large number of robots is mitigated by employing a graph convolutional neural (GCN) network to parametrize policies for the robots. The GCN reduces the dimensionality of the problem by learning filters that aggregate information among robots locally, similar to how a convolutional neural network is able to learn local features in an image. Additionally, by employing a GCN we are also able to overcome the computational overhead of training policies for a large number of robots by first training graph filters for a small number of robots followed by zero-shot policy transfer to a larger number of robots. We demonstrate the effectiveness of our framework through various simulations.


page 1

page 5


Large Scale Distributed Collaborative Unlabeled Motion Planning with Graph Policy Gradients

In this paper, we present a learning method to solve the unlabelled moti...

Graph Policy Gradients for Large Scale Robot Control

In this paper, we consider the problem of learning policies to control a...

Learning Safe Unlabeled Multi-Robot Planning with Motion Constraints

In this paper, we present a learning approach to goal assignment and tra...

Motion Planning for Variable Topology Trusses: Reconfiguration and Locomotion

Truss robots are highly redundant parallel robotic systems and can be ap...

Hypergraph-based Multi-Robot Task and Motion Planning

We present a multi-robot task and motion planning method that, when appl...

A Clinical Dataset for the Evaluation of Motion Planners in Medical Applications

The prospect of using autonomous robots to enhance the capabilities of p...

Cooperative 2D Reconfiguration using Spatio-Temporal Planning and Load Transferring

We present progress on the problem of reconfiguring a 2D arrangement of ...

Please sign up or login with your details

Forgot password? Click here to reset