Haptic Shared Control (HSC) can improve operator performance during teleoperation. HSC uses assistive forces on the master device to guide the operator's control input towards a reference trajectory. However, the reference trajectory might be incorrect due to inaccuracies in the sensed or modeled environment and thus not match the intended trajectory of the operator, resulting in force conflicts that can potentially reduce performance. This paper describes the design and evaluation of a haptic shared controller whose reference trajectory adapts in real-time to resort force conflicts. Different adaptive controllers have been designed and compared in simulation. The final controller is built on a Task Parameterized Gaussian Mixture Model and adapts using an Incremental Gaussian Mixture Model. The controller is evaluated in an experiment (n=16) where subjects performed a planar teleoperation task that involved moving the slave through a narrow corridor. The subjects were assisted by HSC with a correct reference (cHSC), HSC with a wrong reference (wHSC), HSC with a wrong reference that adapts in real-time (waHSC) and a manual condition.
The waHSC condition was expected to result in lower control effort, compared to wHSC, and induce better performance compared to wHSC and the manual condition.
Within-subjects results showed that waHSC decreases control effort compared to wHSC, while the performance remained similar. Manual control had better performance than wHSC and waHSC, and cHSC outperformed all other conditions.
Even though the conditions were tested in a balanced order, we observed a strong effect of the order of the conditions: between-subject results showed improved performance, lower control effort and better subjective results for waHSC over wHSC when wHSC was executed first. Upon first execution of waHSC, improved performance and self-reported satisfaction were realized for wHSC over waHSC. The results show that, in the event of a force conflict, an adaptive controller is a promising alternative to temporarily adjusting the HSC stiffness.

In this thesis, a swarm is defined as: ”A swarm is a large number of homogenous, unsophisticated agents that interact locally among themselves and their environment, without any central control or management to yield a global behaviour to emerge.” The bigger perspective is to have the units within a swarm operate for a potentially infinite amount of time, thus making algorithms and energy use as effective as possible. The research is split up in different sections: sensors, communication and behaviour. The behaviour is split again: individual behaviour, anti collision behaviour and swarming behaviour. The research on the sensors and communication points out that the Bluetooth Low Energy (BLE) sensor is the most suitable for an autonomous Zebro Swarm. BLE can be used to transfer data as well as serve as a range sensor. As a communication device, BLE offers the ability to advertise data an has a range of 50 meters which is sufficient for application in a swarm. As a sensor, BLE offers fairly accurate measurements in distances below 1 meter. Due to the properties of radio signal strength and the always present radio frequency noise, the accuracy decreased with increasing distances. The individual behaviour aims at exploring as much area as possible, with the amount of energy available. The energy use therefore has to be minimised and the explored area maximised. Since little is known on the energy use, this is assumed constant. Maximising area, however, has some key elements. The first is to keep moving; standing still results in energy use without exploring new terrain. The second is to make only gentle turns; the rotational centre must be outside of the detection distance. When this centre lies inside of the detection distance, the inner turn will cover area for a longer period making the turn ineffective. The anti collision behaviour should prevent units from making physical contact. By using a contactless sensor an approaching collision can be detected. Changing the parameters of the movement of the units at the moment they enclose more than a certain value prevents the collision. The anti separation behaviour should prevent units from separating from eachother. This can be done by making units turn 180 degrees once the relative distance reaches a certain limit. The turning on a certain limit is a simple algorithm and thus requires little processing power. Apart from the anti collision behaviour and the anti separation behaviour, there is another approach to deal with these behaviours. Since the units are able to communicate with each other, they can also advertise their location to other units. There are several methods for a unit to acquire their location. These methods are divided in approximate and exact location estimation methods. The Trial and Error method is placed in the first category, the exact location estimation methods are: Time Based, Internal Reference, External Reference and Radar. The External Reference method is considered the most applicable of these methods since it is relatively accurate, simple and provides a direct location.