Arrow Research search

Author name cluster

Nathan Brooks

Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.

3 papers
2 author rows

Possible papers

3

AAMAS Conference 2013 Conference Paper

An Approach to Team Programming with Markup for Operator Interaction

  • Nathan Brooks
  • Ewart de Visser
  • Timur Chabuk
  • Elan Freedy
  • Paul Scerri

This paper presents a team plan specification language that combines work in the creation of generic team plans and design of intelligent interfaces. Two motivations the language are (1) to combine inter-agent cooperation and operator interaction of complex behaviors into a single plan, and (2) to separate plan design and UI design such that they are created by application domain experts and human interaction experts, respectively. The result is a generic language for multi-robot plans that defines tasks to be performed, interactions for maintaining situational awareness, and mixed initiative reactions to operator workload.

IROS Conference 2012 Conference Paper

Scheduling operator attention for Multi-Robot Control

  • Shih Yi Chien
  • Michael Lewis 0001
  • Siddharth Mehrotra
  • Nathan Brooks
  • Katia P. Sycara

A wide class of multirobot control tasks involves operator interactions with individual robots. Where the robots' actions are independent, as for example in some foraging tasks, the operator can interact with robots sequentially in a round robin fashion. If the need for interaction can be detected by the robot through self-reflection, the robot could communicate its need for interaction to the operator. The resulting human-robot system would form a queuing system in which the operator is the server and the queue of robots requesting interaction, the jobs. As a queuing system, performance could be optimized using standard techniques, providing the operator's attention could be appropriately directed. An earlier study found that Human-Robot Interaction (HRI) performance was improved by communicating requests for interaction to the operator, however, a first-in-first-out (FIFO) aid showing a single request at a time led to poorer performance than one showing the entire (Open) queue. The current experiment compared Open-queue and FIFO conditions from the first experiment with a Priority-queue using a shortest job first (SJF) discipline known to maximize throughput. Performance in the Priority-queue condition was statistically indistinguishable from the best performance for all measures except those for missed victims where it was intermediate between FIFO (best) and Open-queue. Both of the other conditions produced poorest performance on some measures. The results suggest that operator attention can be effectively scheduled allowing the use of scheduling algorithms to improve the efficiency of HRI.

AAMAS Conference 2011 Conference Paper

Allocating Spatially Distributed Tasks in Large, Dynamic Robot Teams

  • Steven Okamoto
  • Nathan Brooks
  • Sean Owens
  • Katia Sycara
  • Paul Scerri

For an interesting class of emerging applications, a large robot team will need to distributedly allocate many more tasks than there are robots, with dynamically appearing tasks and a limited ability to communicate. The LA-DCOP algorithm can conceptually handle both large-scale problems and multiple tasks per robot, but has key limitations when allocating spatially distributed tasks. In this paper, we extend LA-DCOP with several alternative acceptance rules for robots to determine whether to take on an additional task, given the interaction with the tasks it has already committed to. We show that these acceptance rules dramatically outperform a naive LA-DCOP implementation. In addition, we developed a technique that lets the robots use completely local knowledge to adjust their task acceptance criteria to get the best possible performance at a given communication bandwidth level.

v2026.09.13