Communication-Aware Robotics
Students: Arjun Muralidharan and Herbert Cai, Advisor: Yasamin Mostofi, UCSB
Multi-agent systems, Fundamentals of the co-optimization of sensing, communication, and navigation for successful task accomplishments under resource constraints | Utilizing unmanned vehicles to enable new forms of connectivity: (top) robotic routers, (bottom) robotic beam forming | Fundamentals of wireless channel predictability in realistic communication environments, optimal path planning for a connectivity-seeking robot |
For more than a decade, our lab has been very excited about the possibilities created at the intersection of communications and robotics. Consider the general problem where a team of unmanned vehicles are given a task to do cooperatively. As such, maintaining some form of connectivity, among the nodes or to an outside node, can be crucial to the successful task accomplishment. Since path planning decisions of the robots can directly affect the connectivity, the unmanned vehicles need to take connectivity no.s into account when path planning. We then have the following important question: how should each robot make decisions that co-optimize navigation, communication, and sensing no.s properly, under resource constraints? In another example, consider using unmanned vehicles to enable a needed form of connectivity. More specifically, can a group of unmanned vehicles path plan to form a network that supports the needed connectivity? We have coined the term communication-aware robotics more than a decade ago to refer to such a body of problems created at the intersection of the two areas of robotics and communications. In order to properly solve such problems, tools from both areas of robotics and communications are needed. Furthermore, impact of realistic communication channels on robotic networks should be considered by considering factors such as multipath fading, shadowing, and path loss. In IEEE ICRA 2010 and IEEE TWC 2012, we have then shown how an unmanned vehicle can go beyond the typically-used but unrealistic disk models, and realistically predict the channel at unvisited locations, using a probabilistic framework (Gaussian process). Our approach has been extensively validated experimentally. This then opens up new possibilities for the co-optimization of communication and navigation in robotic operations, as we discuss next. See the publications for a complete list of our papers in this area.
Consider an unmanned vehicle that is not connected in its current spot. What are the statistics of the distance to connectivity (first passage distance)? In IEEE ACC 2017, we have mathematically characterized the PDF of the distance to connectivity, using stochastic differential equations and stochastic dynamic programming. Next, can this robot find a connected spot with minimal energy consumptions, without knowledge of the exact channel quality over the field, and in realistic channel environments that can experience multipath, shadowing, and path loss? In IEEE Globecom 2017 and submitted journal, we have shown how to optimally solve this problem (the first such result to the best of our knowledge) by formulating it as an infinite horizon Markov Decision Process problem. We have then proposed a path planner, using a game-theoretic framework, that asymptotically gets arbitrarily close to the optimal solution, but with a considerably less space complexity. It is noteworthy that our formulation is very general in this paper and addresses the general problem of minimizing the expected cost till success, where the success can be connectivity or other robotic goals.
Next, consider a number of unmanned vehicles. What are the fundamentals of utilizing mobility to enable new forms of network connectivity? In IEEE TCNS 2017, we have proposed a novel way of enabling connectivity, using a number of mobile robots that do cooperative beam forming. More specifically, we have shown how each robot should optimize its motion to move to a place better for cooperative robotic beam forming. This enables the unmanned vehicles to establish a strong link, with a minimal energy usage, although each individual one cannot establish the needed connectivity on its own. In IEEE TRO 2012, we have then shown how a number of unmanned vehicles can optimally path plan to act as robotic routers and establish a robust information flow between two otherwise remote nodes.
Next, consider a team of unmanned vehicles that is tasked with a mission in realistic communication environments that experience fading, shadowing, and path loss. The path of the robots affects both communication and sensing qualities. Thus, the communication, navigation, and sensing no.s should be co-optimized, especially in resource-constrained environments. Along this line, we have recently proposed (IEEE TCNS 2018) a new methodology for the co-optimization of sensing, communication and navigation objectives in a networked robotic operation, based on an optimal-control approach. More specifically, consider a team of robots tasked with collectively transmitting a given amount of data to a remote station, while operating in realistic communication environments that experience path loss, shadowing, and multipath fading. We have shown how to optimally design the load distribution, paths, and transmission power/rate schedules of the robots in a way that minimizes the total energy required for motion and communication. In IEEE TWC 2013, we have also considered this problem from an optimization theory perspective and shown underlying properties of the optimum motion-communication solution using KKT conditions. Overall, our methodology allows the robots to accomplish the given task in harsh environments, and with minimum resources in terms of total energy consumption, operation time, etc.
In IEEE TSP 2012 and IEEE TAC 2011, two specific application examples are considered: cooperative robotic surveillance (IEEE TSP 2012) and cooperative target tracking (IEEE TAC 2011), where some of our communication-aware design methodologies were tailored to these specific applications, to enable robust cooperative operation in realistic communication environments. Finally, the "To go or Not to go" problem was addressed in IEEE TCNS 2014. In many situations, an unmanned vehicle can incur motion energy to move to a better place for connectivity, or can increase its transmission power. While it is the general belief that motion will always be more expensive, we have shown (in IEEE TCNS 2014) under what conditions on the channel and motion parameters, it is more energy-efficient for the robot to incur motion energy to enable connectivity, and other what conditions it should simply increase its transmission power. As we have shown, there are several instances where it is more energy-efficient for the robot to incur motion energy and find a connected spot.
See the publications below for more details.
Our research has resulted in several wireless channel measurements collected with our robots during our experiments. We have released some of our channel data, which can be useful for testing robotic approaches in realistic channel environments. You can find the released data here.
We have furthermore developed a realistic wireless channel simulator that can generate simulated 2D wireless channels by properly modeling the three underlying dynamics of a wireless channel, which are path loss, shadowing and multipath fading. You can find the corresponding codes here.
W. Hurst, H. Cai, and Y. Mostofi, "Communication-Aware RRT*: Path Planning for Robotic Communication Operation in Obstacle Environments," IEEE International Conference on Communications (ICC) , June 2021.[pdf]
A. Muralidharan and Y. Mostofi, "Communication-Aware Robotics: Exploiting Motion for Communication," Invited paper, to appear, Annual Reviews (AR) of Control, Robotics, and Autonomous Systems, 2020.[pdf]
A. Muralidharan and Y. Mostofi, "Statistics of the Distance Traveled until Connectivity for Unmanned Vehicles," Autonomous Robots, Jan. 2020.[pdf][bibtex]
A. Muralidharan and Y. Mostofi, "Path Planning for Minimizing the Expected Cost till Success," IEEE Transactions on Robotics, volume 35, issue 2, April 2019.[pdf][bibtex]
U. Ali, H. Cai, Y. Mostofi and Y. Wardi, "Motion-Communication Co-optimization with Cooperative Load Transfer in Mobile Robotics: an Optimal Control Perspective," IEEE Transactions on Control of Network Systems, volume 6, issue 2, June 2019.[pdf][bibtex]
A. Muralidharan and Y. Mostofi, "Energy Optimal Distributed Beamforming using Unmanned Vehicles," IEEE Transactions on Control of Network Systems, 2017.[pdf][bibtex]
A. Muralidharan and Y. Mostofi, "Path Planning for a Connectivity Seeking Robot," in the proceedings of IEEE Globecom, Workshop on Wireless Networking for Unmanned Autonomous Vehicles, December 2017.[pdf][bibtex]
A. Muralidharan and Y. Mostofi, "First Passage Distance to Connectivity for Mobile Robots," invited paper, in the proceedings of the American Control Conference (ACC), May 2017.[pdf][bibtex]
U. Ali, H. Cai, Y. Mostofi and Y. Wardi, "Motion and Communication Co-Optimization with Path Planning and Online Channel Estimation," in the proceedings of the American Control Conference (ACC), July 2016.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Efficient Clustering and Path Planning Strategies for Robotic Data Collection Using Space-Filling Curves," IEEE Transactions on Control of Network Systems, May 2016.[pdf][bibtex]
A. Muralidharan and Y. Mostofi, "Distributed Beamforming Using Mobile Robots," in the proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), invited paper, March 2016.[pdf][bibtex]
A. Muralidharan, Y. Yan and Y. Mostofi, "Binary Log-Linear Learning With Stochastic Communication Links," in the proceedings of IEEE Military Communications Conference (MILCOM), invited paper, 2015.[pdf][bibtex]
U. Ali, Y. Yan, Y. Mostofi, and Y. Wardi, "An Optimal Control Approach for Communication and Motion Co-optimization in Realistic Fading Environments," in the proceedings of American Control Conference (ACC), pp. 2930 - 2935, July 2015.[pdf][bibtex]
Y. Yan and Y. Mostofi, "An Efficient Clustering and Path Planning Strategy in Sensor Networks for Data Collection Based on Space-Filling Curves," in the proceedings of IEEE Conference on Decision and Control (CDC), Dec. 2014. [pdf][bibtex]
Y. Yan and Y. Mostofi, "To Go or Not to Go: On Energy-aware and Communication-aware Robotic Operation," IEEE Transactions on Control of Network Systems, vol. 1, no. 3, pp. 218-231, July 2014.[pdf][bibtex]
P. Twu, Y. Mostofi, and M. Egerstedt, "A Measure of Heterogeneity in Multi-Agent Systems," in proceedings of the American Control Conference (ACC), June 2014.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Efficient Communication-Aware Dynamic Coverage Using Space-Filling Curves," in the proceedings of American Control Conference (ACC), June 2014. [pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "Dynamic Networked Coverage of Time-Varying Environments in the Presence of Fading Communication Channels," ACM Transactions on Sensor Networks, vol. 10, no. 3, April 2014.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Impact of Localization Errors on Wireless Channel Prediction in Mobile Robotic Networks," in the proceedings of IEEE Globecom, Workshop on Wireless Networking for Unmanned Autonomous Vehicles, Dec. 2013.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Communication and Path Planning Strategies of a Robotic Coverage Operation," in the proceedings of American Control Conference (ACC), June 2013.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Co-Optimization of Communication and Motion Planning of a Robotic Operation under Resource Constraints and in Fading Environments", IEEE Transactions on Wireless Communications, vol. 12, no. 4, April 2013.[pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "Optimal Motion and Communication for Persistent Information Collection using a Mobile Robot," in the proceedings of the IEEE Globecom, Workshop on Wireless Networking for Unmanned Autonomous Vehicles, Dec. 2012.[pdf][bibtex]
Mehrzad Malmirchegini, A. Ghaffarkhah, and Y. Mostofi, "Impact of Motion and Channel Parameters on the Estimation of Transmitter Position in Robotic Networks," in the proceedings of the IEEE Globecom, Workshop on Wireless Networking for Unmanned Autonomous Vehicles, Dec. 2012.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Utilizing Mobility to Minimize the Total Communication and Motion Energy Consumption of a Robotic Operation," in the proceedings of the World Congress of the International Federation of Automatic Control (IFAC), Workshop on Distributed Estimation and Control in Networked Systems, Sept. 2012.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Robotic Router Formation in Realistic Communication Environments," IEEE Transactions on Robotics, vol. 28, no. 4, pp. 810-827, August 2012.[pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "Path Planning for Networked Robotic Surveillance," IEEE Transactions on Signal Processing, vol. 60, no. 7, pp. 3560-3575, July 2012. [pdf][bibtex]
M. Malmirchegini and Y. Mostofi, "An Integrated Sparsity and Model-Based Probabilistic Framework For Estimating the Spatial Variations of Communication Channels," Special Issue of Elsevier Physical Communication Journal on Compressive Sensing in Communications, vol. 5, no. 2, June 2012. [pdf][bibtex]
M. Malmirchegini and Y. Mostofi, "On the Spatial Predictability of Communication Channels," IEEE Transactions on Wireless Communications, vol.11, no.3, pp. 964-978, March 2012.[pdf][bibtex][sample data]
A. Ghaffarkhah, Yuan Yan, and Y. Mostofi, "Dynamic Coverage of Time-varying Environments using a Mobile Robot -- A Communication-Aware Perspective," in the proceedings of IEEE Globecom, Workshop on Wireless Networking for Unmanned Autonomous Vehicles, Dec. 2011.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Co-Optimization of Communication and Motion Planning of a Robotic Operation in Fading Environments," invited paper, in the proceedings of Asilomar Conference on Signals, Systems, and Computers, Dec. 2011.[pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "A Communication-Aware Framework for Robotic Field Exploration," in the proceedings of IEEE Conference on Decision and Control (CDC), 2011.[pdf][bibtex]
N. Bezzo, Y. Yan, R. Fierro, and Y. Mostofi, "A decentralized connectivity strategy for mobile router swarms", World Congress of the International Federation of Automatic Control (IFAC), 2011.
A. Gonzalez-Ruiz, A. Ghaffarkhah, and Y. Mostofi, "A Comprehensive Overview and Characterization of Wireless Channels for Networked Robotic and Control Systems,"Journal of Robotics, vol. 2011, October 2011. [pdf][bibtex][channel simulator]
A. Ghaffarkhah and Y. Mostofi, "Communication-Aware Motion Planning in Mobile Networks," IEEE Transactions on Automatic Control, Special Issue on Wireless Sensor and Actuator Networks, vol. 56, no. 10, pp. 2478-2485, Oct. 2011.[pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "Communication-Aware Surveillance in Mobile Sensor Networks," in the proceedings of American Control Conference (ACC), June 2011. [pdf][bibtex]
Y. Mostofi and A. Ghaffarkhah, "Kalman Filtering over Wireless Fading Channels," book chapter, in Wireless Network Based Control (editor: Sudip Mazumder), Springer, December 2010.[pdf][bibtex]
Y. Yan and Y. Mostofi, "Robotic Router Formation - A Bit Error Rate Approach," in the proceedings of the IEEE Military Communications Conference (MILCOM), Oct. 2010. [pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "Channel Learning and Communication-Aware Motion Planning in Mobile Networks," in the proceedings of the American Control Conference (ACC), July 2010. [pdf][bibtex]
Y. Mostofi, M. Malmirchegini and A. Ghaffarkhah, "Estimation of Communication Signal Strength in Robotic Networks," in the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), May 2010. [pdf][bibtex]
Y. Mostofi, "Decentralized Communication-Aware Motion Planning in Mobile Networks: An Information-Gain Approach," Journal of Intelligent and Robotic Systems, Special Issue on Unmanned Autonomous Vehicles, vol. 56, no. 2, 2009. [pdf][bibtex]
Y. Mostofi and R. Murray, "Kalman Filtering over Wireless Fading Channels - How to Handle Packet Drop," International Journal of Robust and Nonlinear Control, Special Issue on Control with Limited Information, vol. 19, pp. 1993-2015, 2009. [pdf][bibtex]
M. Malmirchegini and Y. Mostofi, "Fusion and Diversity Trade-offs in Cooperative Estimation over Fading Channels," in the proceedings of the IEEE Globecom, 2009. [pdf][bibtex]
Y. Mostofi, A. Gonzalez-Ruiz, A. Ghaffarkhah, and D. Li, "Characterization and Modeling of Wireless Channels for Networked Robotic and Control Systems - A Comprehensive Overview," in the proceedings of the International Conference on Intelligent Robots and Systems (IROS), 2009. [pdf] [bibtex] [channel simulator]
A. Ghaffarkhah and Y. Mostofi, "Communication-Aware Navigation Functions for Robotic Networks," in the proceedings of the American Control Conference (ACC), 2009. [pdf][bibtex]
A. Ghaffarkhah and Y. Mostofi, "Communication-Aware Motion Planning of Robotic Networks using Navigation Functions," in the proceedings of the International Conference on Robot Communication and Coordination (RoboComm), 2009. [pdf][bibtex]
J. Fink, T. Collins, V. Kumar, Y. Mostofi, J. Baras and B. Sadler, "A Simulation Environment for Modeling and Development of Algorithms for Ensembles of Mobile Microsystems," in the proceedings of the SPIE Conference on Micro- and Nanotechnology Sensors, Systems, and Applications, April 2009. [bibtex]
Y. Mostofi and R. Murray, "To Drop or Not to Drop: Design Principles for Kalman Filtering over Wireless Fading Channels," IEEE Transactions on Automatic Control, vol. 54, no. 2, pp. 376-381, Feb. 2009. [pdf][bibtex]
Y. Mostofi and P. Sen, "Compressed Signal Strength Mapping," in the proceedings of the IEEE Military Communications Conference (MILCOM), November 2008. [pdf][bibtex]
Y. Mostofi, "Communication-Aware Motion Planning in Fading Environments," in the proceedings of the IEEE International Conference on Robotics and Automation (ICRA), May 2008. [pdf][bibtex]
Y. Mostofi and R. Murray, "Communication and Sensing Trade-Offs in Cooperative Mobile Networks," Asian Journal of Control, Special Issue on Collective Behavior and Control of Multi-Agent Systems, vol. 10, no. 2, pp. 156-170, March 2008. [pdf][bibtex]
Y. Mostofi and R. Murray, "To Drop or Not to Drop, Receiver Design Principles for Estimation over Wireless Links," invited paper, in the proceedings of the American Control Conference (ACC), June 2007. [pdf][bibtex]
Y. Mostofi and R. Murray, "Distributed Sensing and Estimation under Communication Constraints," in the proceedings of the IEEE Conference on Decision and Control (CDC), Dec. 2006, San Diego, CA. [pdf][bibtex]
Y. Mostofi and R. Murray, "Optimum Allocation of Computing Resources in Networked Sensing and Control," best paper in the session, in proceedings of the American Control Conference (ACC), Minneapolis, MN, June 2006.[pdf][bibtex]
Y. Mostofi and R. Murray, "New Design Principles for Estimation over Fading Channels in Mobile Sensor Networks," invited paper, in the proceedings of the IEEE Conference on Decision and Control(CDC), Dec. 2005, Seville, Spain. [pdf][bibtex]
Y. Mostofi and R. Murray, "On Dropping Noisy Packets in Kalman Filtering Over a Wireless Fading Channel," best paper in the session, Proceedings of 24th American Control Conference (ACC), June 2005,
Y. Mostofi, T. Chung, R. Murray and J. Burdick, "Communication and Sensing Trade Offs in Decentralized Mobile Sensor Networks: A Cross-Layer Design Approach," in the proceedings of the International Conference on Information Processing in Sensor Networks (IPSN), April 2005,
Y. Mostofi and R. Murray, "Effect of Time-Varying Fading Channels on the Control Performance of a Mobile Sensor Node," in the proceedings of the IEEE International Conference on Sensor and Ad Hoc Communications and Networks (Secon), October 2004, Santa Clara, CA. [pdf][bibtex]