Human-Robot Collaboration is the study of collaborative processes in human and robot agents work together to achieve shared goals. Many new applications for robots require them to work alongside people as capable members of human-robot teams. These include robots for homes, hospitals, and offices, space exploration and manufacturing.
Human-Robot Collaboration (HRC) is an interdisciplinary research area comprising classical robotics, human-computer interaction, artificial intelligence, design, cognitive sciences and psychology.
Industrial applications of human-robot collaboration involve Collaborative Robots, or cobots, that physically interact with humans in a shared workspace to complete tasks such as collaborative manipulation or object handovers.
For effective human-robot collaboration, it is imperative that the robot is capable of understanding and interpreting several communication mechanisms similar to the mechanisms involved in human-human interaction. The robot must also communicate its own set of intents and goals to establish and maintain a set of shared beliefs and to coordinate its actions to execute the shared plan. In addition, all team members demonstrate commitment to doing their own part, to the others doing theirs, and to the success of the overall task.
Human-human collaborative activities are studied in depth in order to identify the characteristics that enable humans to successfully work together. These activity models usually aim to understand how people work together in teams, how they form intentions and achieve a joint goal. Theories on collaboration inform human-robot collaboration research to develop efficient and fluent collaborative agents.
The approaches to human-robot collaboration include human emulation (HE) and human complementary (HC) approaches. Although these approaches have differences, there are research efforts to develop a unified approach stemming from potential convergences such as Collaborative Control.
The human emulation approach aims to enable computers to act like humans or have human-like abilities in order to collaborate with humans. It focuses on developing formal models of human-human collaboration and applying these models to human-computer collaboration. In this approach, humans are viewed as rational agents who form and execute plans for achieving their goals and infer other people’s plans.
The human complementary approach seeks to improve human-computer interaction by making the computer a more intelligent partner that complements and collaborates with humans. The premise is that the computer and humans have fundamentally asymmetric abilities.
Key Aspects are :
- Specialization of Roles- Based on the level of autonomy and intervention, there are several human-robot relationships including master-slave, supervisor–subordinate, partner–partner, teacher–learner and fully autonomous robot.
- Establishing shared goal(s)- Through direct discussion about goals or inference from statements and actions, agents must determine the shared goals they are trying to achieve.
- Allocation of Responsibility and Coordination- Agents must decide how to achieve their goals, determine what actions will be done by each agent, and how to coordinate the actions of individual agents and integrate their results.
- Shared context- Agents must be able to track progress toward their goals. They must keep track of what has been achieved and what remains to be done.
- Communication- Any collaboration requires communication to define goals, negotiate over how to proceed and who will do what, and evaluate progress and results.
- Adaptation and learning- Collaboration over time require partners to adapt themselves to each other and learn from one’s partner both directly or indirectly.
- Time and space- The time-space taxonomy divides human-robot interaction into four categories based on whether the humans and robots are using computing systems at the same time (synchronous) or different times (asynchronous) and while in the same place (collocated) or in different places (non-collocated).
- Ergonomics- Human factors and ergonomics are one of the key aspects for a sustainable human-robot collaboration. The robot control system can use biomechanical models and sensors to optimize various ergonomic metrics, such as muscle fatigue.