TL;DR
This paper enhances Pepper robot's social interaction by integrating advanced hardware like NVIDIA Jetson and RealSense camera, along with perception algorithms, to improve human detection, localization, and interaction capabilities.
Contribution
It introduces hardware upgrades and perception algorithms for Pepper, enabling real-time human detection and interaction improvements on extended hardware.
Findings
Enhanced human detection and localization accuracy
Real-time processing with NVIDIA Jetson GPU
Validated perception algorithms with MoCap dataset
Abstract
In this paper, we propose hardware and software enhancements for the Pepper robot to improve its human-robot interaction capabilities. This includes the integration of an NVIDIA Jetson GPU to enhance computational capabilities and execute real time algorithms, and a RealSense D435i camera to capture depth images, as well as the computer vision algorithms to detect and localize the humans around the robot and estimate their body orientation and gaze direction. The new stack is implemented on ROS and is running on the extended Pepper hardware, and the communication with the robot s firmware is done through the NAOqi ROS driver API. We have also collected a MoCap dataset of human activities in a controlled environment, together with the corresponding RGB-D data, to validate the proposed perception algorithms.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
