Today's technology still limits the accessing to 2D information (images, graphics, charts, maps, paintings, etc.) for visually impaired people (VIP). Existing solutions for human-machine interfaces are expensive and have yet to be available to the many. Therefore, we propose a novel and inclusive haptic architecture to access and interact with 2D data, relying on the force-feedback principle, and named Force-Feedback Tablet (F2T). The F2T's architecture is based on a flat thumbstick mounted on a 2D actuated support, enabling force feedback effects on user's finger. The flat thumbstick measures the user's intended movements independently from mobile support's actual movements, enabling highly interactive effects, static and dynamic effects, or guidances. Moreover, the mechanical structure does not need to be backdrivable, simplifying the motion control, and reducing the costs of the device. Finally, the F2T architecture allows designing lightweight, compact and scalable devices. To validate and demonstrate the relevance of the F2T architecture, we present two lightweight prototypes. Two series of preliminary tests with VIP and blindfolded participants confirmed the system's effectiveness at providing shape and spatial layout understanding. Results obtained during the evaluation are encouraging with high recognition rates.

This paper presents a novel bio-inspired predictive model of visual navigation inspired by mammalian navigation. This model takes inspiration from specific types of neurons observed in the brain, namely place cells, grid cells and head direction cells. In the proposed model, place cells are structures that store and connect local representations of the explored environment, grid and head direction cells make predictions based on these representations to define the position of the agent in a place cell’s reference frame. This specific use of navigation cells has three advantages: First, the environment representations are stored by place cells and require only a few spatialized descriptors or elements, making this model suitable for the integration of large-scale environments (indoor and outdoor). Second, the grid cell modules act as an efficient visual and absolute odometry system. Finally, the model provides sequential spatial tracking that can integrate and track an agent in redundant environments or environments with very few or no distinctive cues, while being very robust to environmental changes. This paper focuses on the architecture formalization and the main elements and properties of this model. The model has been successfully validated on basic functions: mapping, guidance, homing, and finding shortcuts. The precision of the estimated position of the agent and the robustness to environmental changes during navigation were shown to be satisfactory. The proposed predictive model is intended to be used on autonomous platforms, but also to assist visually impaired people in their mobility.

This paper introduces the design of a novel indoor and outdoor mobility assistance system for visually impaired people. This system is named the MAPS (Mobility Assistance Path Planning and orientation in Space), and it is based on the theoretical frameworks of mobility and spatial cognition. Its originality comes from the assistance of two main functions of navigation: locomotion and wayfinding. Locomotion involves the ability to avoid obstacles, while wayfinding involves the orientation in space and ad hoc path planning in an (unknown) environment. The MAPS architecture proposes a new low-cost system for indoor–outdoor cognitive mobility assistance, relying on two cooperating hardware feedbacks: the Force Feedback Tablet (F2T) and the TactiBelt. F2T is an electromechanical tablet using haptic effects that allow the exploration of images and maps. It is used to assist with maps’ learning, space awareness emergence, path planning, wayfinding and effective journey completion. It helps a VIP construct a mental map of their environment. TactiBelt is a vibrotactile belt providing active support for the path integration strategy while navigating; it assists the VIP localize the nearest obstacles in real-time and provides the ego-directions to reach the destination. Technology used for acquiring the information about the surrounding space is based on vision (cameras) and is defined with the localization on a map. The preliminary evaluations of the MAPS focused on the interaction with the environment and on feedback from the users (blindfolded participants) to confirm its effectiveness in a simulated environment (a labyrinth). Those lead-users easily interpreted the system’s provided data that they considered relevant for effective independent navigation.