No abstract

The tracking of people is an indispensable capacity in almost any robotic application. A relevant case is the @home robotic competitions, where the service robots have to demonstrate that they possess certain skills that allow them to interact with the environment and the people who occupy it; for example, receiving the people who knock at the door and attending them as appropriate. Many of these skills are based on the ability to detect and track a person. It is a challenging problem, particularly when implemented using low-definition sensors, such as Laser Imaging Detection and Ranging (LIDAR) sensors, in environments where there are several people interacting. This work describes a solution based on a single LIDAR sensor to maintain a continuous identification of a person in time and space. The system described is based on the People Tracker package, aka PeTra, which uses a convolutional neural network to identify person legs in complex environments. A new feature has been included within the system to correlate over time the people location estimates by using a Kalman filter. To validate the solution, a set of experiments have been carried out in a test environment certified by the European Robotic League.

Socially assistive robots have been used in the care of elderly or dependent people, particularly with patients suffering from neurological diseases, like autism and dementia. There are some proposals, but there are no standardized mechanisms for assessing a particular robot’s suitability for specific therapy. This paper reports the evaluation of an acceptance test for assistive robots applied to people with dementia. The proposed test focuses on evaluating the suitability of a robot during therapy sessions. The test measures the rejection of the robot by the patient based on observational data. This test would recommend what kind of robot and what functionalities can be used in therapy. The novelty of this approach is the formalization of a specific validation process that only considers the reaction of the person to whom the robot is applied, and may be used more effectively than existing tests, which may not be adequate for evaluating assistance robots. The test’s feasibility was tested by applying it to a set of dementia patients in a specialized care facility.

No abstract

No abstract