As robots become more autonomous, their roles shift from being operated and controlled by humans to interactively teaming with humans. The current research focuses on how human operators can effectively team with autonomous urban search and rescue agents in a dynamic and complex task environment. To do so, we empirically examined how shared cognition and restricted language capabilities impacted performance of human-robot dyad search teams using a simulated Minecraft task environment. In order to examine the effects of shared mental models and language the following modified conditions were applied: (1) participants were either able to communicate using natural language or the internal participant's communication was limited to three-word utterances; and (2) shared mental models were manipulated by either the internal participant being made fully aware of the external participant's restricted representation of the environment and inaccurate map or the internal was unaware of these challenges. The primary findings from this study are: (1) teams in the natural language and shared mental model conditions performed better than teams in the limited language and restricted model conditions; (2) when the internal participant was unaware of the challenges of the external, the external perceived higher workload than when there was a shared mental model; (3) teams with natural language and shared mental model demonstrated more predictable behavior than the other teams; (4) some amount of systems’ predictability was good but too much predictability was not good. Overall, these results indicate that effective team interaction and shared cognition play an important role in human-robot dyadic teaming performance.

随着机器人变得更加自主，它们的角色从人工操作和控制转变为与人工交互协作。当前的研究重点是人类操作员如何在动态和复杂的任务环境中有效地与自主的城市搜救人员合作。为此，我们使用模拟的Minecraft任务环境，通过经验研究了共享的认知和受限的语言功能如何影响人机二分搜索引擎的性能。为了检查共享的心理模型和语言的效果，应用了以下修改的条件：（1）参与者要么能够使用自然语言进行交流，要么内部参与者的交流仅限于三个单词的话语；（2）通过使内部参与者充分意识到外部参与者对环境的局限性表示和不正确的地图来操纵共享的心理模型，或者内部参与者没有意识到这些挑战。这项研究的主要发现是：（1）在自然语言和共享心理模型条件下的团队表现优于在有限语言和有限模型条件下的团队；（2）当内部参与者不知道外部的挑战时，外部的工作量要比共享心智模型时要高；（3）具有自然语言和共同心智模式的团队表现出比其他团队更可预测的行为；（4）某些系统的可预测性很好，但太多的可预测性不好。总体，