Improving Human Interaction with Robot Teams
Abstract
This proposal is towards support of our research goal to understand effective human-autonomyteaming architectures and strategies for DoD relevant applications that consider current andfuture abilities of the autonomy, mission requirements, and human cognitive capabilities andlimitations so as to provide high quality human-autonomy system performance. Based on acognitive constraint-based formal framework we seek to perform investigation of key questionsof Human Multi-Robot Interaction. Such questions include: (a) How can operator’s attention beallocated to the multi-robot system without overwhelming the operator? (b) How can theoperator impart intent to the multi-robot system? (c) How can the operator estimate the currentand future states of the multi-robot system so as to decide what actions to take? (d) How can theoperator predict the effect of her actions on the future states and behavior of the system? (e) Howcan the operator correctly calibrate trust to the system? (f) What is the best time for the operatorto give input to the system? (g) How can the operator interact with the system in task switchingor intermittent communication without losing situation awareness (SA)? (h) What types andcontent of media are most effective for operator system interaction? (i) How does robotheterogeneity impact the human interaction? (j) How is the interaction impacted with changingplatform ability in terms of on-board computation, robot-coordination algorithms, and sensorymotorcapabilities? We have studied many of these questions both in simulation and throughindoor navigation with homogeneous robots.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 09, 2018
- Source ID
- FA95501810043
Entities
People
- Katia Sycara
Organizations
- Air Force Office of Scientific Research
- Massachusetts Institute of Technology
- United States Air Force