Experimental study on a smart wheelchair system using a combination of stereoscopic and spherical vision.

This paper is concerned with the experimental study performance of a smart wheelchair system named TIM (Thought-controlled Intelligent Machine), which uses a unique camera configuration for vision. Included in this configuration are stereoscopic cameras for 3-Dimensional (3D) depth perception and mapping ahead of the wheelchair, and a spherical camera system for 360-degrees of monocular vision. The camera combination provides obstacle detection and mapping in unknown environments during real-time autonomous navigation of the wheelchair. With the integration of hands-free wheelchair control technology, designed as control methods for people with severe physical disability, the smart wheelchair system can assist the user with automated guidance during navigation. An experimental study on this system was conducted with a total of 10 participants, consisting of 8 able-bodied subjects and 2 tetraplegic (C-6 to C-7) subjects. The hands-free control technologies utilized for this testing were a head-movement controller (HMC) and a brain-computer interface (BCI). The results showed the assistance of TIM's automated guidance system had a statistically significant reduction effect (p-value = 0.000533) on the completion times of the obstacle course presented in the experimental study, as compared to the test runs conducted without the assistance of TIM.

Real-time performance of a hands-free semi-autonomous wheelchair system using a combination of stereoscopic and spherical vision.

This paper is concerned with the operational performance of a semi-autonomous wheelchair system named TIM (Thought-controlled Intelligent Machine), which uses cameras in a system configuration modeled on the vision system of a horse. This new camera configuration utilizes stereoscopic vision for 3-Dimensional (3D) depth perception and mapping ahead of the wheelchair, combined with a spherical camera system for 360-degrees of monocular vision. The unique combination allows for static components of an unknown environment to be mapped and any surrounding dynamic obstacles to be detected, during real-time autonomous navigation, minimizing blind-spots and preventing accidental collisions with people or obstacles. Combining this vision system with a shared control strategy provides intelligent assistive guidance during wheelchair navigation, and can accompany any hands-free wheelchair control technology for people with severe physical disability. Testing of this system in crowded dynamic environments has displayed the feasibility and real-time performance of this system when assisting hands-free control technologies, in this case being a proof-of-concept brain-computer interface (BCI).

Performance of dry electrode with bristle in recording EEG rhythms across brain state changes.

In this paper we evaluate the physiological performance of a silver-silver chloride dry electrode with bristle (B-Electrode) in recording EEG data. For this purpose, we compare the performance of the bristle electrode in recording EEG data with the standard wet gold-plated cup electrode (G-Electrode) using two different brain state change tasks including resting condition with eyes-closed and performing mathematical task with eyes-open. Using a 2 channel recording device, eyes-closed command data were collected from each of 6 participants for a period of 20 sec and the same procedure was applied for the mathematical calculation task. These data were used for statistical and classification analyse. Although, B-electrode has shown a slightly higher performance compared with G-electrode in both tasks, but analyse did not reveal any significant differences between both electrodes in all six subjects tested.

Semi-autonomous wheelchair developed using a unique camera system configuration biologically inspired by equine vision.

This paper is concerned with the design and development of a semi-autonomous wheelchair system using cameras in a system configuration modeled on the vision system of a horse. This new camera configuration utilizes stereoscopic vision for 3-Dimensional (3D) depth perception and mapping ahead of the wheelchair, combined with a spherical camera system for 360-degrees of monocular vision. This unique combination allows for static components of an unknown environment to be mapped and any surrounding dynamic obstacles to be detected, during real-time autonomous navigation, minimizing blind-spots and preventing accidental collisions with people or obstacles. This novel vision system combined with shared control strategies provides intelligent assistive guidance during wheelchair navigation and can accompany any hands-free wheelchair control technology. Leading up to experimental trials with patients at the Royal Rehabilitation Centre (RRC) in Ryde, results have displayed the effectiveness of this system to assist the user in navigating safely within the RRC whilst avoiding potential collisions.

Spherical vision cameras in a semi-autonomous wheelchair system.

This paper is concerned with the methods developed for extending the capabilities of a spherical vision camera system to allow detection of surrounding objects and whether or not they pose a danger for movement in that direction during autonomous navigation of a power wheelchair. A Point Grey Research (PGR) Ladybug2 spherical vision camera system was attached to the power wheelchair for surrounding vision. The objective is to use this Ladybug2 system to provide information about obstacles all around the wheelchair and aid the automated decision-making process involved during navigation. Through instantaneous neural network classification of individual camera images to determine whether obstacles are present, detection of obstacles have been successfully achieved with accuracies reaching 96%. This assistive technology has the purpose of automated obstacle detection, navigational path planning and decision-making, and collision avoidance during navigation.

Semi-autonomous wheelchair system using stereoscopic cameras.

This paper is concerned with the design and development of a semi-autonomous wheelchair system using stereoscopic cameras to assist hands-free control technologies for severely disabled people. The stereoscopic cameras capture an image from both the left and right cameras, which are then processed with a Sum of Absolute Differences (SAD) correlation algorithm to establish correspondence between image features in the different views of the scene. This is used to produce a stereo disparity image containing information about the depth of objects away from the camera in the image. A geometric projection algorithm is then used to generate a 3-Dimensional (3D) point map, placing pixels of the disparity image in 3D space. This is then converted to a 2-Dimensional (2D) depth map allowing objects in the scene to be viewed and a safe travel path for the wheelchair to be planned and followed based on the user's commands. This assistive technology utilising stereoscopic cameras has the purpose of automated obstacle detection, path planning and following, and collision avoidance during navigation. Experimental results obtained in an indoor environment displayed the effectiveness of this assistive technology.

Bayesian recursive algorithm for width estimation of freespace for a power wheelchair using stereoscopic cameras.

This paper is concerned with the estimation of freespace based on a Bayesian recursive (BR) algorithm for an autonomous wheelchair using stereoscopic cameras by severely disabled people. A stereo disparity map processed from both the left and right camera images is constructed to generate a 3D point map through a geometric projection algorithm. This is then converted to a 2D distance map for the purpose of freespace estimation. The width of freespace is estimated using a BR algorithm based on uncertainty information and control data. Given the probabilities of this width computed, a possible movement decision is then made for the mobile wheelchair. Experimental results obtained in an indoor environment show the effectiveness of this estimation algorithm.

Real-time obstacle detection for an autonomous wheelchair using stereoscopic cameras.

This paper is concerned with the development of a real-time obstacle avoidance system for an autonomous wheelchair using stereoscopic cameras by severely disabled people. Based on the left and right images captured from stereoscopic cameras mounted on the wheelchair, the optimal disparity is computed using the Sum of Absolute Differences (SAD) correlation method. From this disparity, a 3D depth map is constructed based on a geometric projection algorithm. A 2D map converted from this 3D map can then be employed to provide an effective obstacle avoidance strategy for this wheelchair. Experiment results obtained in a practical environment show the effectiveness of this real-time implementation.