An Improved Active SLAM Algorithm for MultiRobot Exploration

An Improved Active SLAM Algorithm for Multi-Robot Exploration Viet-Cuong Pham and Jyh-Ching Juang National Cheng Kung University, Taiwan September 16, 2011 SICE 2011 Tokyo, Japan 國立成功大學 電機 程學系 機電整合實驗室 Supported by: Taiwan National Science Council Naional Cheng Kung University

Outline 1. Introduction 2. Active SLAM problem with multiple robots 3. Proposed approach v General framework v Exploration phase with global optimization strategy v Relocalization phase v Adaptive uncertainty threshold v Limited communication range 4. Simulations and Discussions 5. Conclusions 國立成功大學 電機 程學系 機電整合實驗室 Page 2

1. Introduction üExploration v Robots cover the environment with their sensors üSLAM (Simultaneous Localization and Mapping) v A mobile robot attempts to build a map v At the same time uses this map to deduce its location üOrdinary SLAMs v Only process perceived sensor data v Do not influence the motion of the mobile robot üPath control strategy can have a substantial impact on the quality of the resulting map This study: blend concepts of SLAM, active path planning, and cooperation among multiple robots 國立成功大學 電機 程學系 機電整合實驗室 Page 3

1. Introduction Comparison of different exploration methods Robot system Single Multiple Cooperative SLAM References No No Yes Active No No Multiple Yes Passive [9], [10], [11], [17] [21] [6], [7], [8], [13], [14], [15], [18], [20], [22] [2], [3], [16], [19] Multiple Yes Active [12], this study 國立成功大學 電機 程學系 機電整合實驗室 Page 4

2. Active SLAM problem with multiple robots The state vector : pose of the r-th robot at time k : position of the l-th landmark 國立成功大學 電機 程學系 機電整合實驗室 Page 5

2. Active SLAM problem with multiple robots ü Process model: ü Measurement model: 國立成功大學 電機 程學系 機電整合實驗室 Page 6

2. Active SLAM problem with multiple robots üObjectives: v Cover the whole environment in a minimum amount of time v Guarantee the accuracy of the map Constrained optimization problem : pose error covariance of the r-th robot α : predefined threshold 國立成功大學 電機 程學系 機電整合實驗室 Page 7

3. Proposed approach General framework ü Two parts: v Path generation: determining a target point for each robot v SLAM operation ü Two-phase process 國立成功大學 電機 程學系 機電整合實驗室 Page 8

3. Proposed approach Exploration phase ü Frontier-based exploration ü Existing method: v Disperse robots at local level v Assume a priori knowledge of the environment ü Proposed: Global optimization strategy v Globally disperse robots v Do not assume a priori knowledge of the environment 國立成功大學 電機 程學系 機電整合實驗室 Page 9

3. Proposed approach Exploration phase ü Objective function : utility of information : utility of localizability (distinguish between target points with different localization quality) : cost of navigation : weighting factors : penalty coefficient : assignment matrix ü Determine A: integer programming problem 國立成功大學 電機 程學系 機電整合實驗室 Page 10

3. Proposed approach Relocalization phase ü Objective: maintain the accuracy of the map ü Robot switches to relocalization phase when pose uncertainty becomes large v Revisit previously seen landmarks v Rendezvous with other robots 國立成功大學 電機 程學系 機電整合實驗室 Page 11

3. Proposed approach Relocalization phase ü Objective function : utility of localizability : cost of navigation : loss due to interruption of exploration task (if other robots involved) : distance to the nearest exploration point : weighting factors 國立成功大學 電機 程學系 機電整合實驗室 Page 12

3. Proposed approach Relocalization phase ü r-th robot: revisit A or meet s-th robot at C? A ü D: to assess the effort needed to go back to perform exploration 國立成功大學 電機 程學系 機電整合實驗室 Page 13

3. Proposed approach Adaptive uncertainty threshold ü Fixed threshold α: robots may get stuck in regions with few or no landmarks ü Repeatedly switching between exploration and relocalization phases 國立成功大學 電機 程學系 機電整合實驗室 Page 14

3. Proposed approach Adaptive uncertainty threshold ü Temporary increase the uncertainty threshold ü Threshold should be reduced asap: avoid large error in the exploration process afterwards. ü When to reduce? v Robot pose uncertainty decreases v Landmark density is high 國立成功大學 電機 程學系 機電整合實驗室 Page 15

3. Proposed approach Limited communication range ü Keep robots within communication range? ü Robots are allowed to temporary move out of the communication range and rendezvous later ü Objective function for choosing rendezvous point : utility of localizability : cost of navigation : distance to the nearest exploration point : weighting factors 國立成功大學 電機 程學系 機電整合實驗室 Page 16

4. Simulations & Discussions ü Noise covariance matrices ü Destination is recomputed whenever a robot reached its current destination or a robot has moved 3 m ü Control signals: applied every 0. 025 s ü Range and bearing measurements: taken every 0. 2 s ü Mean velocity of the robots: 3 m/s ü Sensor range: 20 m ü No. of runs: 20 國立成功大學 電機 程學系 機電整合實驗室 Page 17

4. Simulations & Discussions Global optimization strategy ü Case A (proposed): global ü Case B: without global optimization strategy 國立成功大學 電機 程學系 機電整合實驗室 Page 18

4. Simulations & Discussions Global optimization strategy 64. 6% 國立成功大學 電機 程學系 機電整合實驗室 Page 19

4. Simulations & Discussions Adaptive uncertainty threshold 國立成功大學 電機 程學系 機電整合實驗室 A snap-shot of an unfinished exploration mission with fixed uncertainty threshold Page 20 (Case C)

4. Simulations & Discussions Limited communication range 國立成功大學 電機 程學系 機電整合實驗室 Page 21

4. Simulations & Discussions Limited communication range Case G: robots are allowed to move out of communication, no rendezvous 國立成功大學 電機 程學系 機電整合實驗室 Case H: robots are allowed to move out of communication and rendezvous later Page 22

5. Conclusions ü An improved active SLAM algorithm for multi-robot exploration is presented ü Three important improvements: v A global optimization strategy in the exploration phase v An adaptive strategy: automatically adjust the threshold of the robot pose uncertainty constraints v Rendezvous technique: deal with the limited communication range problem ü Improved approach outperforms the original one 國立成功大學 電機 程學系 機電整合實驗室 Page 23

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References Thank you for your attention! 國立成功大學 電機 程學系 機電整合實驗室 Page 26