3D path planning with novel multiple 2D layered approach for complex human-robot interaction

Navigating cluttered indoor environments is a difficult problem in indoor service robotics. The Acroboter concept, a novel approach to indoor locomotion, represents unique opportunity to avoid obstacles in indoor environments by navigating the ceiling plane. This mode of locomotion requires the ability to accurately detect obstacles, and plan 3D trajectories through the environment. This paper presents the development of a resilient object tracking system, as well as a novel approach to generating 3D paths suitable for such robot configurations. Distributed human-machine interfacing allowing simulation previewing of actions is also considered in the developed system architecture.

Uncanny Valley revisited

The 'Uncanny Valley' was conceived in 1970 by Prof Masahiro Mori and details a possible relationship between an object's appearance or motion and how people perceive the object. Initially this research was used without validation. Modern technology has enabled initial investigations, summarised here, that conclude further work is required. A good design guideline for humanoid robots is desired if humanoid robots are to assist with an increasingly elderly population, but not yet possible due to technological constraints. Prosthetics is considered a good resource as the user interaction is comparable to the anticipated level of human-robot interaction and there is a wide range of existing devices.

Robot-human interaction - practical experiments with a cyborg

This paper presents results to indicate the potential applications of a direct connection between the human nervous system and a computer network. Actual experimental results obtained from a human subject study are given, with emphasis placed on the direct interaction between the human nervous system and possible extra-sensory input. An brief overview of the general state of neural implants is given, as well as a range of application areas considered. An overall view is also taken as to what may be possible with implant technology as a general purpose human-computer interface for the future.

The future of human-machine interaction: implant technology

In this paper a look is taken at how the use of implant and electrode technology can be employed to create biological brains for robots, to enable human enhancement and to diminish the effects of certain neural illnesses. In all cases the end result is to increase the range of abilities of the recipients. An indication is given of a number of areas in which such technology has already had a profound effect, a key element being the need for a clear interface linking a biological brain directly with computer technology. The emphasis is placed on practical scientific studies that have been and are being undertaken and reported on. The area of focus is the use of electrode technology, where either a connection is made directly with the cerebral cortex and/or nervous system or where implants into the human body are involved. The paper also considers robots that have biological brains in which human neurons can be employed as the sole thinking machine for a real world robot body.

Molecule modeling of human pentameric alpha(7) neuronal nicotinic acetylcholine receptor and its interaction with its agonist and competitive antagonist

The nicotinic Acetylcholine Receptor (nAChR) is the major class of neurotransmitter receptors that is involved in many neurodegenerative conditions such as schizophrenia, Alzheimer's and Parkinson's diseases. The N-terminal region or Ligand Binding Domain (LBD) of nAChR is located at pre- and post-synaptic nervous system, which mediates synaptic transmission. nAChR acts as the drug target for agonist and competitive antagonist molecules that modulate signal transmission at the nerve terminals. Based on Acetylcholine Binding Protein (AChBP) from Lymnea stagnalis as the structural template, the homology modeling approach was carried out to build three dimensional model of the N-terminal region of human alpha(7)nAChR. This theoretical model is an assembly of five alpha(7) subunits with 5 fold axis symmetry, constituting a channel, with the binding picket present at the interface region of the subunits. alpha-netlrotoxin is a potent nAChR competitive antagonist that readily blocks the channel resulting in paralysis. The molecular interaction of alpha-Bungarotoxin, a long chain alpha-neurotoxin from (Bungarus multicinctus) and human alpha(7)nAChR seas studied. Agonists such as acetylcholine, nicotine, which are used in it diverse array of biological activities, such as enhancements of cognitive performances, were also docked with the theoretical model of human alpha(7)nAChR. These docked complexes were analyzed further for identifying the crucial residues involved in interaction. These results provide the details of interaction of agonists and competitive antagonists with three dimensional model of the N-terminal region of human alpha(7)nAChR and thereby point to the design of novel lead compounds.

Agonist-selective, receptor-specific interaction of human P-2Y receptors with beta-arrestin-1 and-2

Interaction of G-protein-coupled receptors with beta-arrestins is an important step in receptor desensitization and in triggering "alternative" signals. By means of confocal microscopy and fluorescence resonance energy transfer, we have investigated the internalization of the human P2Y receptors 1, 2, 4, 6, 11, and 12 and their interaction with beta-arrestin-1 and -2. Co-transfection of each individual P2Y receptor with beta-arrestin-1-GFP or beta-arrestin-2-YFP into HEK-293 cells and stimulation with the corresponding agonists resulted in a receptor-specific interaction pattern. The P2Y(1) receptor stimulated with ADP strongly translocated beta-arrestin-2-YFP, whereas only a slight translocation was observed for beta-arrestin-1-GFP. The P2Y(4) receptor exhibited equally strong translocation for beta-arrestin-1-GFP and beta-arrestin-2YFP when stimulated with UTP. The P2Y(6), P2Y(11), and P2Y(12) receptor internalized only when GRK2 was additionally cotransfected, but beta-arrestin translocation was only visible for the P2Y(6) and P2Y(11) receptor. The P2Y(2) receptor showed a beta-arrestin translocation pattern that was dependent on the agonist used for stimulation. UTP translocated beta-arrestin-1-GFP and beta-arrestin-2-YFP equally well, whereas ATP translocated beta-arrestin-1-GFP to a much lower extent than beta-arrestin2- YFP. The same agonist-dependent pattern was seen in fluorescence resonance energy transfer experiments between the fluorescently labeled P2Y(2) receptor and beta-arrestins. Thus, the P2Y(2) receptor would be classified as a class A receptor when stimulated with ATP or as a class B receptor when stimulated with UTP. The ligand-specific recruitment of beta-arrestins by ATP and UTP stimulation of P2Y(2) receptors was further found to result in differential stimulation of ERK phosphorylation. This suggests that the two different agonists induce distinct active states of this receptor that show differential interactions with beta-arrestins.

Towards natural human computer interaction in BCI

BCI systems require correct classification of signals interpreted from the brain for useful operation. To this end this paper investigates a method proposed in [1] to correctly classify a series of images presented to a group of subjects in [2]. We show that it is possible to use the proposed methods to correctly recognise the original stimuli presented to a subject from analysis of their EEG. Additionally we use a verification set to show that the trained classification method can be applied to a different set of data. We go on to investigate the issue of invariance in EEG signals. That is, the brain representation of similar stimuli is recognisable across different subjects. Finally we consider the usefulness of the methods investigated towards an improved BCI system and discuss how it could potentially lead to great improvements in the ease of use for the end user by offering an alternative, more intuitive control based mode of operation.

Upper limb robot mediated stroke therapy - GENTLE/s approach

Stroke is a leading cause of disability in particular affecting older people. Although the causes of stroke are well known and it is possible to reduce these risks, there is still a need to improve rehabilitation techniques. Early studies in the literature suggest that early intensive therapies can enhance a patient's recovery. According to physiotherapy literature, attention and motivation are key factors for motor relearning following stroke. Machine mediated therapy offers the potential to improve the outcome of stroke patients engaged on rehabilitation for upper limb motor impairment. Haptic interfaces are a particular group of robots that are attractive due to their ability to safely interact with humans. They can enhance traditional therapy tools, provide therapy "on demand" and can present accurate objective measurements of a patient's progression. Our recent studies suggest the use of tele-presence and VR-based systems can potentially motivate patients to exercise for longer periods of time. The creation of human-like trajectories is essential for retraining upper limb movements of people that have lost manipulation functions following stroke. By coupling models for human arm movement with haptic interfaces and VR technology it is possible to create a new class of robot mediated neuro rehabilitation tools. This paper provides an overview on different approaches to robot mediated therapy and describes a system based on haptics and virtual reality visualisation techniques, where particular emphasis is given to different control strategies for interaction derived from minimum jerk theory and the aid of virtual and mixed reality based exercises.

Bi-directional human machine interface via direct neural connection

This paper presents an application study into the use of a bi-directional link with the human nervous system by means of an implant, positioned through neurosurgery. Various applications are described including the interaction of neural signals with an articulated hand, a group of cooperative autonomous robots and to control the movement of a mobile platform. The microelectrode array implant itself is described in detail. Consideration is given to a wider range of possible robot mechanisms, which could interact with the human nervous system through the same technique.