Date post: | 12-Jan-2016 |
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Solving the Indoor SLAM Problem for a Low-Cost Robot Using Sensor Data Fusion and Autonomous Feature-Based Exploration
PhD Student: Prof. MSc. Luciano Buonocore (UFMA)Advisor: Prof. Dr. Cairo Lúcio Nascimento Júnior (ITA)
Three software modules run in an integrated form
Environment features measured
3 motions usingOdometric model from goal selected
Estimated map at the moment
- 3 types of sensors: a)Visual (wireless CAM + Laser)b)Infrared (two units) c)Sonar
- Softwares:a)PC: overall system intelligence (SLAM filter, Data fusion and Autonomous Exploration).b) Robot: Mutli-Threading C code that executes basic commands, distance measures and some status.
- Communication PC-robot: IP Wireless.
PROPOSED SENSOR DATA FUSION ALGORITHM Experiment to evaluate the mapping accuracy of the algorithm
PROPOSED AUTONOMOUS FEATURE-BASED EXPLORATION
Basic tasks: a)Goals select →locally (1) or environment opening (2)b)Finish condition (of the exploration task)
SLAM EXPERIMENT IN A SMALL INDOOR ENVIRONMENT
WITHOUT AUTONOMOUS EXPLORATION WITH AUTONOMOUS EXPLORATION
RESULTS: •The estimated and real robot poses differences in both experiments are less than 2%.•The map generated by the filter are similar and consistent for navigation purpose.
NEXT EXPERIMENT:•The solution to SLAM problem is already in progress (hallway of 80 m with some loops situations) to validate the algorithms proposed.
EXAMPLE OF DATA PROCESSING IN FUSION ALGORITHM FOR AN SPECIFIC ROBOT POSE