at a given instant and noted if it is within some accepted bound. If it is not, the estimated states of the robot are calculated using equations of dynamics and kinematics at some future time. The process of entering observation data into the model to generate initial conditions is called initialization. The process of initialization for adaptive collaborative control occurs differently depending on the environment: robotics only and human-robotic interaction. Under a robotics only environment, initialization occurs very similarly to the description above. The robotics, systems, subsystems, non-human entities observe some state it finds not in accordance with the higher-level strategy. The entities that are aware of this error use the appropriate equations to present a revised value for a future time step to its peers. For human-robotic interactions, initialization can occur at two different levels. The first level is what was previously described. In this instance, the robot notices some anomaly in its states that is not wholly consistent or is problematic with its higher-level strategy. It queries the human seeking advice to regulate its dilemma. In the other case, the human feels cause to either query some aspect of the robot's state (e.g. health, trajectory, speed) or present advice to the robot that is challenged against the robot's existing tactical approach to the higher-level strategy. The main inputs for adaptive collaborative control are a human-initiated dialogue based command or value presented by either a human or robotic element. The inputs used in the system models serve as the starting point for the collaboration. A number of ways are available to gather observational data for use in functional models. The easiest method to gather observational data is simple human observation of the robotic system. Self-monitoring attributes such as built-in test (BIT) can provide regular reports on important system characteristics. A common approach to gather observations is to employ sensors throughout the robotic system. Vehicles operating in teleoperations have speedometers to indicate how fast they travel. Robotic systems with either stochastic or cyclic motion often employ accelerometers to note the forces exerted. GPS sensors provide a standardized data type that is used nearly universally for depicting location. Multi-sensor systems have been used to gather heterogeneous observational data for applications in path planning. Computation Adaptive collaborative control is most accurately modeled as a closed loop feedback control system. Closed loop feedback control describes the event where the outputs of a system