Optimal Area Covering by Mobile Robot presented by: Nelly Chkolunov Fentahun Assefa-Dawit Fentahun Assefa-Dawit supervised by: Alexey Talyansky Technion - Israel Institute of Technology Electrical Engineering Faculty Control & Robotics Lab

Introduction Mobile Robot Indoor Applications Covering Problems: off-line on-line Servicing equipment Servicing humans Other Functions

Project Description Study of the main covering algorithms: - deterministic - probabilistic - semi-probabilistic Compare these algorithms Choice one of them and apply on the robot

Tools The Pioneer 1 Mobile Robot Key features: Reliable Portable Plug’N’Play Versatile Supported Software Support Saphira (version 6.1) Pioneer Application Interface (PAI) Visual C/C++ env. Communication Devices Radio Modem Pair

Related Papers I.A. Wagner, M. Lindenbaum and A.M. Bruckstein, “MAC vs. PC - Determinism and Randomness as Complementary Approaches to Robotic Exploration of Continuos Unknown Domains” B. Kuipers and Y. Byun, “A Robot Exploration and Mapping Strategy Based on a Semantic Hierarchy of Spatial Representations” C. Hofner and G. Schmidt, “Path planning and guidance techniques for an autonomous mobile cleaning robot”

finds an uncovered point around the current location marks the covered points MAC (Mark And Cover) - the Deterministic Algorithm time needed to cover region with area A:

Advantages: guaranteed coverage of a connected region awareness of completion very efficient on not too large regions Drawbacks:  vulnerable to physical problems (e.g. sensory errors, dependence on a memory)  not efficient for a large regions MAC (Mark And Cover) (cont.)

randomized algorithm make a short step and then random turn PC ( Probabilistic Covering) average cover time:

PC (cont.) Advantage: almost sensorless (just sensors to identify a collision) Drawbacks:  the average performance is lower than MAC  no awareness of completion

a combination of two first: works as PC globally and as MAC in local steps MAC-PC: A Hybrid Algorithm expected coverage time:

MAC-PC (cont.) Advantage: reasonable tradeoff between the performance of the first method and the robustness of the second one Drawback:  still no guarantees a complete coverage

Our Solution MAC-PC - Semi-Probabilistic Covering 1. Cover local area by applying MAC process from current location 2. Choose a random neighbor from a local area boundary 3. Go there 4. Repeat all mentioned above number of times expected for complete coverage of the total area

Our Solution (cont.) Local Area covering (MAC rule): Preprocessing stage: Sonar check Local area bounds check Processing stage: Backtracking in form of milling Robot trace stored in data base during the local area covering

Our Solution (cont.) Expected Number of Random Steps : Simulations & experiments: assumptions and problems

Summary We studied the area covering problem and its different solutions Applied one of them (MAC-PC) on the Pioneer 1 mobile robot Ran the various tests