Group 12: State of the Art: Difference between revisions

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== Obstacle Avoidance ==
== Obstacle Avoidance ==
After the guide robot has detected and divined all the different obstacles we need to determine a path. When determining a path we need to take into account that we need to avoid all the obstacles and we want the most efficient path. Avoiding all the obstacles is harder than just applying an algorithm because we need to take into account that there will be moving obstacles. This means that after determining a path we need to keep checking all the obstacles and alter the path if needed, instead of determining a path at the beginning we can also go "step by step"........
 
 
 
After the guide robot has detected and defined all the different obstacles we need to determine a path. When determining the path we use obstacle avoidance to ensure the safety of the visually impaired and the obstacles. This is called <ref>Danica Janglová, (2004), Neural Networks in Mobile Robot Motion, ''Inernational Journal of Advanced Robotic Systems'', 15-22, http://journals.sagepub.com.dianus.libr.tue.nl/doi/abs/10.5772/5615</ref>the motion planning problem well know in robotics


== GPS Navigation ==
== GPS Navigation ==

Revision as of 11:10, 21 February 2018

Robotic Guides

The use of dogs to guide the visually impaired comes with some limitations, which have been tried to be solved by developing artificial guidance systems (Kang, Kim, Lee & Bien, 2001). There are two different types of guidance systems, a wear type (e.g. A cane) and a mobile robot type, which mimickes the behaviour of a guide dog. The second type has its own mobility and is separate from the user, but it can be attached to the user in some way. Its mobility gives the ability of active guidance.

Kang et al. (2001) proposed an active guidance method for a guide mobile robot. When the robot is used as a guidance tool it should use a pattern of behaviours, which enables the user to follow the robot easily. Using a fuzzy grid-type local map, to estimate the intentions of the objects and the use of multiobjective decision making are very useful for the robot to accomplish its task. But the current fuzzy grid-type isn’t robust enough, so it should be developed further.

According to (Hersh & Johnson, 2010a) most robotic guides for the visually impaired work on the principle, that the robot changes the direction when an obstacle is detected in its path, the change is communicated to the user by having enough mass for the user to feel the movement through the handle (haptically). The current guides are all wheeled, which are easier to design than legged robots and they are more stable. However, legged robots have the ability to move up and down stairs and walk on uneven terrain. Appearance of the robot is another important characteristic, because user acceptance much depends on it. They investigated which functions the users like to see in the robotic guide, they found that they wanted all the proposed functions, namely: obstacle avoidance, location, navigation, location of goods and reading street names. For the appearance of the robot, it was suggested that it should be as invisible as possible and that it should not attract any attention. But it should be robust, small, lightweight and elegant.

Among travel aids, the guide dog is a popular device for obstacle avoidance, however most travel aids have not yet gone beyond the prototype stage (Hersh & Johnson, 2010b). Localisation is important to determine the robot’s pose (heading direction and coordinates). There are three problems that need to be solved: updating the robot’s position form an initially known pose, from an initially unknown pose and localisation when the robot disappears to a random pose. The two main approaches for modelling the indoor environments are grid based and topological. Most types of robotic guides use the combination of haptics and speech to communicate with the end-users. With haptics they communicate their path of velocity to the users.

Hersh and Johnson (2010b) investigated specifications and the desires of respondents considering them. They found that the battery should be at least 16 hours, but several days was preferred. Furthermore, the robot should recharge without the use of vision and maintenance should be minimal. The robot should be easy to use and it should need little training. The robot should be robust and reliable, so it should be able to cope with different types of weather, water, knocks and uneven terrain. The interface should be accessible and the appearance should be customisable. For the user to be able to feel the movement of the robot a long handle is required.

With use of the guide robot in an assistive mode, the visually impaired was able to find obstacle free moving direction, detect stairs/steps and obtain information of the environment (Capi, Kitani ad Ueki, 2013). When the robot was in a guiding mode it can navigate through non-stationary and dynamic indoor environments by using neural controllers. Navigation in urban environments proposes more challenges than in indoor environments, because the pathway characteristics are varying between narrow to wide pedestrian walkways, squares, junctions etc. To guide the visually impaired to robot has to move with a moderate constant speed (e.g. 0.6 m/s). Furthermore, the motion should be smooth without immediate changes in robot speed.

There are different robots that have been studied as a guiding tool for the visually impaired (e.g. Guidecrane, roji and ROVI) (Cho & Lee, 2012). Force that is transmitted through a stick is used by the user to avoid obstacles, but this causes that the stick also transmits all bumps directly to the user. There has also been a study in which the user follows the robot with a dog leash, then the shock isn’t transmitted due to the flexibility of the leash. However, this results in the robot being unable to acquire information about the location of the user and the robot relative to each other. A robot is needed that follows a cooperative relationship with the user and does not only follow commands.


Environment Preception

Obstacle Avoidance

After the guide robot has detected and defined all the different obstacles we need to determine a path. When determining the path we use obstacle avoidance to ensure the safety of the visually impaired and the obstacles. This is called [1]the motion planning problem well know in robotics

GPS Navigation

Voice Recognition

Robotic Design

  1. Danica Janglová, (2004), Neural Networks in Mobile Robot Motion, Inernational Journal of Advanced Robotic Systems, 15-22, http://journals.sagepub.com.dianus.libr.tue.nl/doi/abs/10.5772/5615