Multi-robot Exploration for Environmental Monitoring: The Resource Constrained Perspective provides readers with the necessary robotics and mathematical tools required to realize the correct architecture. The architecture discussed in the book is not confined to environment monitoring, but can also be extended to search-and-rescue, border patrolling, crowd management and related applications. Several law enforcement agencies have already started to deploy UAVs, but instead of using teleoperated UAVs this book proposes methods to fully automate surveillance missions. Similarly, several government agencies like the US-EPA can benefit from this book by automating the process.
Several challenges when deploying such models in real missions are addressed and solved, thus laying stepping stones towards realizing the architecture proposed. This book will be a great resource for graduate students in Computer Science, Computer Engineering, Robotics, Machine Learning and Mechatronics.
1. Introduction - p. 1 2. 1: Introduction - p. 2 3. 2: Target environment - p. 10 4. 3: Utilizing robots - p. 17 5. 4: Simultaneous Localization and Mapping (SLAM) - p. 29 6. Part II: The essentials: The building blocks - p. 38 7. Introduction - p. 39 8. 5: Preliminaries - p. 40 9. 6: Gaussian process - p. 52 10. 7: Coverage Path Planning (CPP) - p. 74 11. 8: Informative Path Planning (IPP) - p. 84 12. Part III: Mission characterization: How does one define a mission? - p. 99 13. Introduction - p. 101 14. 9: Problem formulation - p. 102 15. 10: Endurance & energy estimation - p. 105 16. 11: Range estimation - p. 112 17. Part IV: Scaling to multiple robots: Multiple robots for efficient coverage - p. 155 18. Introduction - p. 157 19. 12: Multi-robot systems - p. 157 20. 13: Fusion of information from multiple robots - p. 169 21. Part V: Continuous spatio-temporal dynamics: Continuous space-time analytics - p. 190 22. Introduction - p. 191 23. 14: Spatio-temporal analysis - p. 191 24. Part VI: Epilogue: Climax - p. 196 25. Introduction - p. 197 26. 15: Real-world algal bloom monitoring - p. 198 27. 16: Cumulus cloud monitoring - p. 206 28. 17: Search & rescue - p. 210 29. 18: Received signal strength based localization - p. 216 30. 19: Conclusion & discussion - p. 222 31. List of reproduced material - p. 231 32. Index - p. 237
Multi-robot Exploration for Environmental Monitoring: The Resource Constrained Perspective provides readers with the necessary robotics and mathematical tools required to realize the correct architecture. The architecture discussed in the book is not confined to environment monitoring, but can also be extended to search-and-rescue, border patrolling, crowd management and related applications. Several law enforcement agencies have already started to deploy UAVs, but instead of using teleoperated UAVs this book proposes methods to fully automate surveillance missions. Similarly, several government agencies like the US-EPA can benefit from this book by automating the process.
Several challenges when deploying such models in real missions are addressed and solved, thus laying stepping stones towards realizing the architecture proposed. This book will be a great resource for graduate students in Computer Science, Computer Engineering, Robotics, Machine Learning and Mechatronics.
1. Introduction - p. 1 2. 1: Introduction - p. 2 3. 2: Target environment - p. 10 4. 3: Utilizing robots - p. 17 5. 4: Simultaneous Localization and Mapping (SLAM) - p. 29 6. Part II: The essentials: The building blocks - p. 38 7. Introduction - p. 39 8. 5: Preliminaries - p. 40 9. 6: Gaussian process - p. 52 10. 7: Coverage Path Planning (CPP) - p. 74 11. 8: Informative Path Planning (IPP) - p. 84 12. Part III: Mission characterization: How does one define a mission? - p. 99 13. Introduction - p. 101 14. 9: Problem formulation - p. 102 15. 10: Endurance & energy estimation - p. 105 16. 11: Range estimation - p. 112 17. Part IV: Scaling to multiple robots: Multiple robots for efficient coverage - p. 155 18. Introduction - p. 157 19. 12: Multi-robot systems - p. 157 20. 13: Fusion of information from multiple robots - p. 169 21. Part V: Continuous spatio-temporal dynamics: Continuous space-time analytics - p. 190 22. Introduction - p. 191 23. 14: Spatio-temporal analysis - p. 191 24. Part VI: Epilogue: Climax - p. 196 25. Introduction - p. 197 26. 15: Real-world algal bloom monitoring - p. 198 27. 16: Cumulus cloud monitoring - p. 206 28. 17: Search & rescue - p. 210 29. 18: Received signal strength based localization - p. 216 30. 19: Conclusion & discussion - p. 222 31. List of reproduced material - p. 231 32. Index - p. 237
