Equipment Support for Multi-human Multi-robot Interactions
Abstract
We request support for purchasing essential instrumentation to pursue novel research related to capturing, modeling, and simulation of interactions between multiple humans and robots in a shared physical environment. This project will involve development of novel techniques for autonomous navigation of multiple robots among human crowds as well as performing collaborative robot-human tasks. The underlying research will lay the scientific foundation of a new area related to multi-human, multi-robot interaction. Furthermore, the high-end workstations with multiple CPUs and GPUs will also support our current research on computational acoustics and physics-based simulation. This equipment will also support the ongoing research under the following funded projects by Army Research Office (ARO), and will be used in our joint collaborative projects with Army Research Laboratory (ARL), United State Army Corps of Engineers (USACE), and Institute of Creative Technologies (ICT). 1. Efficient Computational Models for Simulating Large-Scale Heterogeneous Crowds (PI: M. Lin; Co-PI: D. Manocha) 2. Efficient Numeric and Geometric Computations using Heterogeneous Shared-Memory Architectures (PI: D. Manocha) In terms of equipment support, we propose to acquire the following high-end workstations with high performance parallel computing capabilities, as well as robots with different sensing capabilities: We request two different types of robots, as they have different capabilities in terms of sensors and navigation capabilities (e.g. speed, locomotion). Similarly, we request to aquire two types of high-end workstations for studying and analyzing workload issues between CPU-GPU clusters. One of them consist of Tesla GPUs that will be used to train deep learning models for perception, navigation and human-robot interaction. Besides multi-human and multi-robot interactions, the techniques developed using the proposed equipment will also be useful for ongoing research projects acoustic and physics-based simulation, virtual reality, artificial intelligence, and multi-agent simulation. i
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 15, 2018
- Source ID
- W911NF1710181
Entities
People
- Dinesh Manocha
Organizations
- Army Contracting Command
- United States Army
- University of North Carolina at Chapel Hill