This paper presents a mapping system that is suitable for small mobile robots. An ad hoc algorithm for mapping based on the Occupancy Grid method has been developed. The algorithm includes some simplifications in order to be used with low-cost hardware resources. The proposed mapping system has been built in order to be completely autonomous and unassisted. The proposal has been tested with a mobile robot that uses infrared sensors to measure distances to obstacles and uses an ultrasonic beacon system for localization, besides wheel encoders. Finally, experimental results are presented.

Low-cost robots are characterized by low computational resources and limited energy supply. Path planning algorithms aim to find the optimal path between two points so the robot consumes as little energy as possible. However, these algorithms were not developed considering computational limitations (i.e., processing and memory capacity). This paper presents the HCTNav path-planning algorithm (HCTLab research group’s navigation algorithm). This algorithm was designed to be run in low-cost robots for indoor navigation. The results of the comparison between HCTNav and the Dijkstra’s algorithms show that HCTNav’s memory peak is nine times lower than Dijkstra’s in maps with more than 150,000 cells.

This is the author’s version of a work that was accepted for publication in Journal of Visual Languages and Computing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Visual Languages and Computing,23, 3, (2012) DOI: 10.1016/j.jvlc.2012.01.003This work presents a new approach to the synthesis of Spanish Sign Language (LSE). Its main contributions are the use of a centralized relational database for storing sign descriptions, the proposal of a new input notation and a new avatar design, the skeleton structure of which improves the synthesis process. The relational database facilitates a highly detailed phonologic description of the signs that include parameter synchronization and timing. The centralized database approach has been introduced to allow the representation of each sign to be validated by the LSE National Institution, FCNSE. The input notation, designated HLSML, presents multiple levels of abstraction compared with current input notations. Redesigned input notation is used to simplify the description and the manual definition of LSE messages. Synthetic messages obtained using our approach have been evaluated by deaf users; in this evaluation a maximum recognition rate of 98.5% was obtained for isolated signs and a recognition rate of 95% was achieved for signed sentences