The presence of autonomous systems is growing at a fast pace and it is impacting many aspects of our lives. Designed to learn and act independently, these systems operate and perform decision-making without human intervention. However, they lack the ability to incorporate users' ethical preferences, which are unique for each individual in society and are required to personalize the decision-making processes. This reduces user trust and prevents autonomous systems from behaving according to the moral beliefs of their end-users. When multiple systems interact with differing ethical preferences, they must negotiate to reach an agreement that satisfies the ethical beliefs of all the parties involved and adjust their behavior consequently. To address this challenge, this paper proposes RobEthiChor, an approach that enables autonomous systems to incorporate user ethical preferences and contextual factors into their decision-making through ethics-based negotiation. RobEthiChor features a domain-agnostic reference architecture for designing autonomous systems capable of ethic-based negotiating. The paper also presents RobEthiChor-Ros, an implementation of RobEthiChor within the Robot Operating System (ROS), which can be deployed on robots to provide them with ethics-based negotiation capabilities. To evaluate our approach, we deployed RobEthiChor-Ros on real robots and ran scenarios where a pair of robots negotiate upon resource contention. Experimental results demonstrate the feasibility and effectiveness of the system in realizing ethics-based negotiation. RobEthiChor allowed robots to reach an agreement in more than 73% of the scenarios with an acceptable negotiation time (0.67s on average). Experiments also demonstrate that the negotiation approach implemented in RobEthiChor is scalable.

翻译：自主系统的应用正以前所未有的速度扩展，深刻影响着我们生活的诸多方面。这些系统被设计为能够独立学习与行动，在无人干预的情况下自主运行并执行决策。然而，它们普遍缺乏融入用户伦理偏好的能力——这种偏好在社会中因人而异，且是实现决策过程个性化所必需的。这一缺陷不仅削弱了用户信任，也阻碍了自主系统按照终端用户的道德信念行事。当多个系统因伦理偏好差异而产生交互时，必须通过协商达成符合各方伦理信念的共识，并据此调整自身行为。为应对这一挑战，本文提出RobEthiChor方法，使自主系统能够通过基于伦理的协商机制，将用户伦理偏好与情境因素纳入决策过程。RobEthiChor提供了一种领域无关的参考架构，用于设计具备伦理协商能力的自主系统。本文同时介绍了RobEthiChor-Ros——该方法是RobEthiChor在机器人操作系统（ROS）中的具体实现，可部署于机器人平台以赋予其基于伦理的协商能力。为评估该方法，我们在真实机器人上部署RobEthiChor-Ros，并构建了多机器人资源竞争场景下的协商实验。实验结果表明：该系统在实现伦理协商方面具备可行性与有效性。在超过73%的实验场景中，机器人能以可接受的协商时间（平均0.67秒）达成共识。实验同时验证了RobEthiChor所实现的协商方法具有良好的可扩展性。