References
- Abraham, I., & Murphey, T. D. (2018). Decentralized ergodic control: distribution-driven sensing and exploration for multiagent systems. IEEE Robotics and Automation Letters, 3(4), 2987–2994. https://doi.org/https://doi.org/10.1109/LRA.2018.2849588
- Adaldo, A., Mansouri, S. S., Kanellakis, C., Dimarogonas, D. V., Johansson, K. H., & Nikolakopoulos, G. (2017). Cooperative coverage for surveillance of 3d structures. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 1838–1845). IEEE.
- Avellar, G. S., Pereira, G. A., Pimenta, L. C., & Iscold, P. (2015). Multi-UAV routing for area coverage and remote sensing with minimum time. Sensors, 15(11), 27783–27803. https://doi.org/https://doi.org/10.3390/s151127783
- Ayvali, E., Salman, H., & Choset, H. (2017). Ergodic coverage in constrained environments using stochastic trajectory optimization. In 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 5204–5210). IEEE.
- Azpúrua, H., Freitas, G. M., Macharet, D. G., & Campos, M. F. (2018). Multi-robot coverage path planning using hexagonal segmentation for geophysical surveys. Robotica, 36(8), 1144–1166. https://doi.org/https://doi.org/10.1017/S0263574718000292
- Best, G., Faigl, J., & Fitch, R. (2018). Online planning for multi-robot active perception with self-organising maps. Autonomous Robots, 42(4), 715–738. https://doi.org/https://doi.org/10.1007/s10514-017-9691-4
- Burgard, W., Moors, M., Stachniss, C., & Schneider, F. E. (2005). Coordinated multi-robot exploration. IEEE Transactions on Robotics, 21(3), 376–386. https://doi.org/https://doi.org/10.1109/TRO.2004.839232
- Chung, T. H., Hollinger, G. A., & Isler, V. (2011). Search and pursuit-evasion in mobile robotics. Autonomous Robots, 31(4), 299. https://doi.org/https://doi.org/10.1007/s10514-011-9241-4
- Couceiro, M. S., Rocha, R. P., & Ferreira, N. M. (2011). A novel multi-robot exploration approach based on particle swarm optimization algorithms. In 2011 IEEE International Symposium on Safety, Security, and Rescue Robotics (pp. 327–332). IEEE.
- Couceiro, M. S., Vargas, P. A., Rocha, R. P., & Ferreira, N. M. (2014). Benchmark of swarm robotics distributed techniques in a search task. Robotics and Autonomous Systems, 62(2), 200–213. https://doi.org/https://doi.org/10.1016/j.robot.2013.10.004
- Cui, R., Li, Y., & Yan, W. (2015). Mutual information-based multi-auv path planning for scalar field sampling using multidimensional RRT. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 46(7), 993–1004. https://doi.org/https://doi.org/10.1109/TSMC.2015.2500027
- Evans, L. C. (1997). Partial differential equations and monge-kantorovich mass transfer. Current Developments in Mathematics, 1997(1), 65–126. https://doi.org/https://doi.org/10.4310/CDM.1997.v1997.n1.a2
- Hollinger, G., Singh, S., Djugash, J., & Kehagias, A. (2009). Efficient multi-robot search for a moving target. The International Journal of Robotics Research, 28(2), 201–219. https://doi.org/https://doi.org/10.1177/0278364908099853
- Hollinger, G. A., & Singh, S. (2012). Multirobot coordination with periodic connectivity: theory and experiments. IEEE Transactions on Robotics, 28(4), 967–973. https://doi.org/https://doi.org/10.1109/TRO.2012.2190178
- Hollinger, G. A., & Sukhatme, G. S. (2014). Sampling-based robotic information gathering algorithms. The International Journal of Robotics Research, 33(9), 1271–1287. https://doi.org/https://doi.org/10.1177/0278364914533443
- Kabir, R. H., & Lee, K. (2020). Receding-horizon ergodic exploration planning using optimal transport theory. In 2020 American Control Conference (ACC) (Vol. 10, pp. 1447–1452). IEEE.
- Kala, R. (2012). Multi-robot path planning using co-evolutionary genetic programming. Expert Systems with Applications, 39(3), 3817–3831. https://doi.org/https://doi.org/10.1016/j.eswa.2011.09.090
- Khan, A. T., & Li, S. (2021). Human guided cooperative robotic agents in smart home using beetle antennae search. SCIENCE CHINA Information Sciences.
- Khan, A. T., Li, S., & Cao, X. (2021a). Control framework for cooperative robots in smart home using bio-inspired neural network. Measurement, 167 (2021), 108253. https://doi.org/https://doi.org/10.1016/j.measurement.2020.108253
- Khan, A. T., Li, S., Kadry, S., & Nam, Y. (2020). Control framework for trajectory planning of soft manipulator using optimized RRT algorithm. IEEE Access, 8(2020), 171730–171743. https://doi.org/https://doi.org/10.1109/Access.6287639
- Khan, A. T., Li, S., & Li, Z. (2021b). Obstacle avoidance and model-free tracking control for home automation using bio-inspired approach. Advanced Control for Applications: Engineering and Industrial Systems, e63. https://doi.org/https://doi.org/10.1002/adc2.63.
- Kwa, H. L., Kit, J. L., & Bouffanais, R. (2020). Optimal swarm strategy for dynamic target search and tracking. In Proceedings of the 19th International Conference on Autonomous Agents and MultiAgent Systems (pp. 672–680). AAMAS.
- Lee, K. (2015). Analysis of large-scale asynchronous switched dynamical systems. PhD thesis.
- Lee, K., & Bhattacharya, R. (2014). Optimal switching synthesis for jump linear systems with gaussian initial state uncertainty. In ASME 2014 Dynamic Systems and Control Conference (pp. V002T24A003–V002T24A003). American Society of Mechanical Engineers.
- Lee, K., & Bhattacharya, R. (2018). Optimal controller switching for resource-constrained dynamical systems. International Journal of Control, Automation and Systems, 16(3), 1323–1331. https://doi.org/https://doi.org/10.1007/s12555-017-0530-3
- Lee, K., Halder, A., & Bhattacharya, R. (2014). Probabilistic robustness analysis of stochastic jump linear systems. In American Control Conference (ACC) (pp. 2638–2643). IEEE.
- Lee, K., Halder, A., & Bhattacharya, R. (2015). Performance and robustness analysis of stochastic jump linear systems using Wasserstein metric. Automatica, 51(2015), 341–347. https://doi.org/https://doi.org/10.1016/j.automatica.2014.10.080
- Lee, K., Martínez, S., Cortés, J., Chen, R. H., & Milam, M. B. (2018). Receding-horizon multi-objective optimization for disaster response. In 2018 Annual American Control Conference (ACC) (pp. 5304–5309). IEEE.
- Li, B., Moridian, B., Kamal, A., Patankar, S., & Mahmoudian, N. (2019a). Multi-robot mission planning with static energy replenishment. Journal of Intelligent & Robotic Systems, 95(2), 745–759. https://doi.org/https://doi.org/10.1007/s10846-018-0897-2
- Li, W., & Shen, W. (2011). Swarm behavior control of mobile multi-robots with wireless sensor networks. Journal of Network and Computer Applications, 34(4), 1398–1407. https://doi.org/https://doi.org/10.1016/j.jnca.2011.03.023
- Li, Z., Li, C., Li, S., & Cao, X. (2019b). A fault-tolerant method for motion planning of industrial redundant manipulator. IEEE Transactions on Industrial Informatics, 16(12), 7469–7478. https://doi.org/https://doi.org/10.1109/TII.9424
- Li, Z., & Li, S. (2020). Saturated pi control for nonlinear system with provable convergence: an optimization perspective. IEEE Transactions on Circuits and Systems II: Express Briefs, 68(2), 742–746. https://doi.org/https://doi.org/10.1109/TCSII.8920
- Li, Z., Zuo, W., & Li, S. (2020). Zeroing dynamics method for motion control of industrial upper-limb exoskeleton system with minimal potential energy modulation. Measurement, 163(2020), 107964. https://doi.org/https://doi.org/10.1016/j.measurement.2020.107964
- Mathew, G., & Mezić, I. (2011). Metrics for ergodicity and design of ergodic dynamics for multi-agent systems. Physica D: Nonlinear Phenomena, 240(4), 432–442. https://doi.org/https://doi.org/10.1016/j.physd.2010.10.010
- Mavrommati, A., Tzorakoleftherakis, E., Abraham, I., & Murphey, T. D. (2017). Real-time area coverage and target localization using receding-horizon ergodic exploration. IEEE Transactions on Robotics, 34(1), 62–80. https://doi.org/https://doi.org/10.1109/TRO.8860
- Miller, L. M., & Murphey, T. D. (2013). Trajectory optimization for continuous ergodic exploration. In 2013 American Control Conference (pp. 4196–4201). IEEE.
- Mohamad, M. M., Dunnigan, M. W., & Taylor, N. K. (2005). Ant colony robot motion planning. In EUROCON 2005-The International Conference on Computer as a Tool (Vol. 1, pp. 213–216). IEEE.
- Nikitenko, A., Grundspenkis, J., Liekna, A., Ekmanis, M., Kulikovskis, G., & Andersone, I. (2014). Multi-robot system for vacuum cleaning domain. In International Conference on Practical Applications of Agents and Multi-Agent Systems (pp. 363–366). Springer.
- Pugh, J., & Martinoli, A. (2007). Inspiring and modeling multi-robot search with particle swarm optimization. In 2007 IEEE Swarm Intelligence Symposium (pp. 332–339). IEEE.
- Ryan, M. R. K. (2008). Exploiting subgraph structure in multi-robot path planning. Journal of Artificial Intelligence Research, 31(2008), 497–542. https://doi.org/https://doi.org/10.1613/jair.2408
- Senanayake, M., Senthooran, I., Barca, J. C., Chung, H., Kamruzzaman, J., & Murshed, M. (2016). Search and tracking algorithms for swarms of robots: a survey. Robotics and Autonomous Systems, 75(2016), 422–434. https://doi.org/https://doi.org/10.1016/j.robot.2015.08.010
- Sheng, W., Yang, Q., Tan, J., & Xi, N. (2006). Distributed multi-robot coordination in area exploration. Robotics and Autonomous Systems, 54(12), 945–955. https://doi.org/https://doi.org/10.1016/j.robot.2006.06.003
- Silverman, Y., Miller, L. M., MacIver, M. A., & Murphey, T. D. (2013). Optimal planning for information acquisition. In 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 5974–5980). IEEE.
- Solovey, K., Salzman, O., & Halperin, D. (2015). Finding a needle in an exponential haystack: discrete RRT for exploration of implicit roadmaps in multi-robot motion planning. In Algorithmic Foundations of Robotics XI (pp. 591–607). Springer.
- Surana, A., Mathew, G., & Kannan, S. (2012). Coverage control of mobile sensors for adaptive search of unknown number of targets. In 2012 IEEE International Conference on Robotics and Automation (pp. 663–670). IEEE.
- Tan, Y., & Zheng, Z.-Y. (2013). Research advance in swarm robotics. Defence Technology, 9(1), 18–39. https://doi.org/https://doi.org/10.1016/j.dt.2013.03.001
- Ulusoy, A., Smith, S. L., Ding, X. C., Belta, C., & Rus, D. (2013). Optimality and robustness in multi-robot path planning with temporal logic constraints. The International Journal of Robotics Research, 32(8), 889–911. https://doi.org/https://doi.org/10.1177/0278364913487931
- Veitch, C., Render, D., & Aravind, A. (2019). Ergodic flocking. In 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) (pp. 6957–6962). IEEE.
- Villani, C. (2008). Optimal transport: old and new (Vol. 338), Springer Science & Business Media.
- Wurm, K. M., Stachniss, C., & Burgard, W. (2008). Coordinated multi-robot exploration using a segmentation of the environment. In 2008 IEEE/RSJ International Conference on Intelligent Robots and Systems (pp. 1160–1165). IEEE.
- Xu, A., Viriyasuthee, C., & Rekleitis, I. (2014). Efficient complete coverage of a known arbitrary environment with applications to aerial operations. Autonomous Robots, 36(4), 365–381. https://doi.org/https://doi.org/10.1007/s10514-013-9364-x
- Yazici, A., Kirlik, G., Parlaktuna, O., & Sipahioglu, A. (2013). A dynamic path planning approach for multirobot sensor-based coverage considering energy constraints. IEEE Transactions on Cybernetics, 44(3), 305–314. https://doi.org/https://doi.org/10.1109/TCYB.6221036
- Yehoshua, R., Agmon, N., & Kaminka, G. A. (2016). Robotic adversarial coverage of known environments. The International Journal of Robotics Research, 35(12), 1419–1444. https://doi.org/https://doi.org/10.1177/0278364915625785
- Zou, R., Kalivarapu, V., Winer, E., Oliver, J., & Bhattacharya, S. (2015). Particle swarm optimization-based source seeking. IEEE Transactions on Automation Science and Engineering, 12(3), 865–875. https://doi.org/https://doi.org/10.1109/TASE.2015.2441746