Brain-Machine Interfaces for Astronauts
Operating machines to perform complex tasks is a common approach in everyday's life. In zero gravity conditions usually even simple tasks can become quite difficult. A machine that reads astronauts' thoughts and puts them into practice would facilitates complex operations in space.
The space environment is inherently hostile and dangerous for astronauts. For this reason, extra-vehicular activity (EVA) should be limited and replaced by robotic systems as much as possible. In addition, it would be desirable to optimize the interface between astronauts and external semi-automatic manipulators and devices. Both the rather rigid space suit and the zero-g environment considerably limit the mobility of the astronaut and hence a reliable hand-free interface would augment both the astronaut's performance and safety.
Status
Currently the application of BMIs are under consideration in diverse fields such as entertainment (computer games) and medicine (prosthetic devices). It is to be expected that BMI technology will experience great progress in the near future.
As human physiology is greatly influenced during space travel our current aim is to examine the applicability of BMIs in micro gravity condition.
In order to assess the effects of microgravity on current BMIs, two members of the ACT and two members of the EPFL institute on Brain Machine Interfaces (IDIAP) performed the first experiment in microgravity, on the Novespace A300-G aircraft. In 31 parabolas with 22 seconds of weighlessness each we examined how Brain Machine Interfaces work under these very particular conditions.
Insect-machine hybrid control architecture
Low level and high level tasks
The difference of performance between a living organism and a conventional robot becomes most apparent in unstructured environments with unknown and potentially hazardous situations occurring in a non-predictable manner. However, unmanned exploratory missions to e.g. mars or the moon are in general preferred to missions with human presence since due to several reasons these missions allow to cross boundaries far beyond that where humans can be brought at an acceptable risk. However, facing the challenges of autonomous exploration, the range of future automated mission vehicles strongly correlates with capability of control architecture to successfully integrate a whole range of decision parameters. In this context we investigate the potential of integrating "animal intelligence" into the control architecture of exploratory vehicles. Our aim is to reproduce both low level mechanisms and higher level decision taking behaviours that are necessary for an insect. The integration of insect intelligence - or the employed mechanisms that lead to emergent intelligence - shall be realized according to their complexity in different manners:
- Elements of short range orientation, such as obstacle avoidance reaction, wall following behaviour, altitude control, etc. were already successfully realized in artificial electronic demonstrators. But the complex decision structures involved in weighing the different inputs from the analogue electronics is still subject to speculation.
- Additionally parameters such as maintaining the energy budget, navigation towards a distant goal, route learning, etc. require a control architecture that obtains a certain flexibility and the ability to autonomously take decisions and revise them: a level of complexity that current control architectures are still far to be successfully managed.
For these high-level tasks we want to examine the potential solution of integrating pre-developed living intelligence, i.e. neuronal circuits taken from the brain of a developed animal.
