This section provides a list of future work proposed to improve the dynamic teleoperation VRUI framework presented in this thesis. The framework currently consists of four separate layers, as discussed in Chapters 3 to 6, respectively. Each of these layers could benefit from a range of future work proposed as follows:
Layer 1 consists of the main virtual control room and the communication platform providing the foundation for the dynamic teleoperation VRUI. Future work for Layer 1 could benefit from work that improves the current cylindrical geometric design of the main virtual control room. For example, a human factor investigation into the current virtual control room design could be undertaken to determine possible design changes and suggestions that would improve the overall interactive efficiency. Such an investigation could also include VR interaction techniques best suited for user selections, particularly the selection and switching of individual robots.
Future work for Layer 2, which is responsible for the auto-categorisation of individual robots, could benefit from the use of more sophisticated soft
computing categorisation techniques. The mixed results obtained when testing the designed ANN and its ability to categorise robots within the more kinematically complex categories of humanoid, torso, and mobile manipulator maybe attributed to the fact that these categories also have several simple kinematic elements. For example, a torso robot consists of two manipulators or a mobile manipulator consists of the combination of a manipulator and a UGV. As such, soft computing categorisation techniques such as SVM or FNN could be used to improve current results obtained from the designed ANN presented in Chapter 4.
Future work for Layer 3, which is responsible for identifying the required number of VRUI configurations for a given robot team, could benefit from an investigation into the representation of motion controls supported by ROS robots. Currently, ROS lacks a standard approach for representing the motion control strategies available on an individual robot within ROS. Moreover, a wide range of ROS messages and nodes available in a range of ROS packages are used to provide motion control strategies for ROS-supported robots. This wide range makes the automatic identification of motion control strategies available on individual ROS robots difficult to ascertain, as well as affects the ability to provide the relationship rules set as described in Layer 3. A proposed approach is using a format similar to the URDF available in ROS to describe all possible motion control strategies available in a single standardised format.
Future work for Layer 4, which is responsible for the dynamic assignment of individual VRUI configurations, could be improved through a system that adapts to the behaviour of teleoperators. One possible approach
could be the assignment of individual user profiles for different teleoperators, with the aim of providing a customised approach to the dynamic assignment of VRUI configurations. For example, if a teleoperator typically uses waypoint control and a LIDAR sensor for the humanoid category of robots, then the system will automatically assign this VRUI configuration when switching control to a humanoid robot rather than the teleoperator making these sensor and motion control selections.
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