# Telepresence Social Robotics towards Co-Presence: A Review
## 3 From Telepresence to Co-Presence Design
### Co-Presence Design
#### 3.1.5 Managing Robot Autonomy in Telepresence Systems  
Advances in robot autonomy do not eliminate the role of human operators. Human skills remain crucial in an unstructured environment or when dealing with unpredicted events. The integration of autonomous mechanisms aims for process simplification, and it changes the nature of human-robot interaction (HRI). However, there are cases where the complexity increases [155] (e.g., 2019 Boeing 737 Max autopilot problems with deadly consequences). The availability of automated behaviors for telepresence or in humanoid robots may lead people to use them indiscriminately, diverting attention from the interaction essentials. Nevertheless, autonomous mechanisms aim to reduce users' mental workload, performing increasingly complex tasks and now being part of our daily lives (e.g., self-driving cars, autonomous vacuum cleaners, and chatbots). The literature refers to methods to integrate autonomy mechanisms in telerobotics [156], and they can be classified into direct control, supervisory control, shared control, traded control, collaborative control, and cooperative control [157; 158]. _Direct control_: The robot has no autonomy. An operator controls all the robot's functions manually. Mirroring is a type of direct control in which the robot replicates the human's movements and expressions. Supervisory control: The robot is programmed intermittently according to the continuous information received from the robot. The human and the robot integrate a closed control loop focused on task performance [159]. Shared control: The human operator controls the robot continuously. However, those commands may be strictly followed by the robot (similar to direct control) or be modified by the robot's system to improve performance or run safely. Collaborative control: The operator and the robot work together as peers to determine the robot's behavior. In [PERSON]'s work [160], there is an explicit semantic dialogue between humans and robots to mediate the sharing of control. Traded control: The human operator starts a behavior or task that is autonomously performed by the robot. At any time, the operator can stop that behavior or task and start a new one. Cooperative control: The behavior of a single robot results from the controlled cooperation of several operators using any of the aforementioned methodologies. In the shared control method, the operator provides continuous commands to the robot, aiming for high-level behavior from the robot. However, the robot may change those inputs to reach the perceived system goals [161]. The method assumes that the operator knows how to direct the robot's high-level behaviors but may not be sufficiently skilled to express the right commands due to a lack of situation awareness, embodiment, telepresence, or lack of robot motor accuracy and sensor information. Typically, the shared control method includes \"safeguard\" mechanisms, in which the operators' command actions are overwritten if they violate the robot's safety rules, such as collision with a wall or person or losing balance [162]. The software of HPR-1s or HRP-5P humanoid robots was developed to discard commands that could make the robot lose balance, limiting joint angles [163; 164; 165]. In [PERSON] et al. [92], given the robot's height, the wheel's initial acceleration provided by the operator had to be supervised by the robot to avoid its falling down. In [PERSON] and [PERSON]'s works, the robot's desired trajectory was provided through a joystick as the intended general direction and not as low-level position commands [166]. In the traded control method, a task or subtask is performed autonomously by the robot, but it is initiated by the operator and may be stopped at any time. The method is useful for simultaneously controlling multiple robot's appendages, such as in teleoperation of humanoids [167; 168; 169]. The Geminoid HI-1 robot [169] relies on a traded control known as state-based control, in which the operator selects the state from a library of states.