Technion — Israel Institute of Technology Electrical Engineering

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

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

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”

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

MAC (Mark And Cover) (cont. ) Advantages: ü guaranteed coverage of a connected region ü awareness of completion ü 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

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

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

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

MAC-PC (cont. ) Advantage: ü 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