Publications by David Julian Gonon

Geometric and Learning Methods for Robots to Navigate in Human Crowds with Application to Smart Mobility Devices

The thesis at hand is concerned with robots' navigation in human crowds. Specifically, methods are developed for planning a mobile robot's local motion between pedestrians, and they are evaluated in experiments where a robot interacts with real pedestrians ...

EPFL2023

Inverse Reinforcement Learning of Pedestrian-Robot Coordination

Aude Billard, David Julian Gonon

We apply inverse reinforcement learning (IRL) with a novel cost feature to the problem of robot navigation in human crowds. Consistent with prior empirical work on pedestrian behavior, the feature anticipates collisions between agents. We efficiently learn ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2023

Robots' Motion Planning in Human Crowds by Acceleration Obstacles

Aude Billard, David Julian Gonon, Diego Felipe Paez Granados

We study the Acceleration Obstacle (AO) as a concept to enable a robot's navigation in human crowds. The AO's geometric properties are analyzed and a direct sampling-free algorithm is proposed to approximate its boundary by linear constraints. The resultin ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022

Pedestrian-Robot Interactions on Autonomous Crowd Navigation: Reactive Control Methods and Evaluation Metrics

Aude Billard, David Julian Gonon, Yujie He

Autonomous navigation in highly populated areas remains a challenging task for robots because of the difficulty in guaranteeing safe interactions with pedestrians in unstructured situations. In this work, we present a crowd navigation control framework tha ...

IEEE2022

Crowd against the machine: A simulation-based benchmark tool to evaluate and compare robot capabilities to navigate a human crowd

Aude Billard, David Julian Gonon, Diego Felipe Paez Granados

The evaluation of robot capabilities to navigate human crowds is essential to conceive new robots intended to operate in public spaces. This paper initiates the development of a benchmark tool to evaluate such capabilities; our long term vision is to provi ...

IEEE2021

Reactive Navigation in Crowds for Non-holonomic Robots with Convex Bounding Shape

Aude Billard, David Julian Gonon, Diego Felipe Paez Granados

This paper describes a novel method for non-holonomic robots of convex shape to avoid imminent collisions with moving obstacles. The method's purpose is to assist navigation in crowds by correcting steering from the robot's path planner or driver. We evalu ...

2021