Anthony Tzes

Collaborative visual area coverage

Abstract This article examines the problem of visual area coverage by a network of Mobile Aerial Agents (MAAs). Each MAA is assumed to be equipped with a downwards facing camera with a conical field of view which covers all points within a circle on the ground. The diameter of that circle is proportional to the altitude of the MAA, whereas the quality of the covered area decreases with the altitude. A distributed control law that maximizes a joint coverage-quality criterion by adjusting the MAAs’ spatial coordinates is developed. The effectiveness of the proposed control scheme is evaluated through simulation studies.

Distributed area coverage control with imprecise robot localization: Simulation and experimental studies

This article examines the static area coverage problem by a network of mobile, sensor-equipped agents with imprecise localization. Each agent has uniform radial sensing ability and is governed by first-order kinodynamics. To partition the region of interest, a novel partitioning scheme, the Additively Weighted Guaranteed Voronoi diagram is introduced which takes into account both the agents’ positioning uncertainty and their heterogeneous sensing performance. Each agent’s region of responsibility corresponds to its Additively Weighted Guaranteed Voronoi cell, bounded by hyperbolic arcs. An appropriate gradient ascent-based control scheme is derived so that it guarantees monotonic increase of a coverage objective and is extended with collision avoidance properties. Additionally, a computationally efficient simplified control scheme is offered that is able to achieve comparable performance. Several simulation studies are offered to evaluate the performance of the two control schemes. Finally, two experiments using small differential drive-like robots and an ultra-wideband positioning system were conducted, highlighting the performance of the proposed control scheme in a real world scenario.

Experimental studies on distributed control for area coverage using mobile robots

This article examines the experimental issues associated with the area coverage problem using a network of mobile robots. The developed schemes in the literature assume an unrealistic perfect knowledge of each point-robots position. To account for the imprecise robots localization, the covered space partitioning relies on the Guaranteed Voronoi (GV) principle, under the assumption of uniform radial sensing for each agent. The distributed nature of the developed algorithm assigns to each robot a GV-cell which is bounded by hyperbolic arcs. The only required information for the implementation of this scheme is the relative positioning from each robot to its GV-Delaunay neighbors. Simulation and experimental studies are offered to highlight the efficiency of the proposed distributed experimental-oriented control law.

Cyber-attack on a power plant using bias injected measurements

This paper addresses the concept of a bias injection cyber-attack on the load frequency control loop of a single-area power plant. The system operates in islanded mode and evolves in the discrete-time domain. A convex and compact set of polyhedral state constraints represents a valid domain of safe operation under the effect of a stabilizing output-feedback dynamic controller. An alarm is triggered whenever the safety constraints are violated, alerting the control center to a potential system intrusion. An attacker succeeds in gaining access to the frequency sensor measurements and corrupts the data transferred to the automatic generation control unit, driving the electrical frequency to a safety-critical steady-state value without triggering an alarm. Simulation studies highlight the effect of the cyber-attack on the physical plant.

Game theoretic optimal position computation of collaborating agents for visual area coverage

The computation problem of the optimal position of collaborating mobile robots equipped with omnidirectional cameras for visual area coverage is the subject of this paper. The planar area has several stationary obstacles resulting in a computationally intractable search scheme. Rather than using gradient-based search methods, the multi-agent swarm is clustered to partially deal with the dimensionality curse. Each cluster is end-to-end connected and its area of responsibility is assigned based on its collective Voronoi tessellation. This area is then coarsely sampled and a game-theoretic approach is employed relying on fictitious play amongst the clusters members. The search scheme is then switched into a fine-spatial sampling and initialized using the previously attained coarse optimal positions of the agents. The provided adaptive-size game-theoretic optimization search approach provides the optimal location of the agents with a tenfold faster convergence compared to the gradient-search methods. Simulation studies are offered to highlight the efficiency of the search scheme.

Synergistic exploration and navigation of mobile robots under pose uncertainty in unknown environments

Path planning under uncertainty in an unknown environment is an arduous task as the resulting map has inaccuracies and a safe path cannot always be found. A path planning method is proposed in unknown environments towards a known target position and under pose uncertainty. A limited range and limited field of view range sensor is considered and the robot pose can be inferred within certain bounds. Based on the sensor measurements a modified map is created to be used for the exploration and path planning processes, taking into account the uncertainty via the calculation of the guaranteed visibility and guaranteed sensed area, where safe navigation can be ensured regardless of the pose-error. A switching navigation function is used to initially explore the space towards the target position, and afterwards, when the target is discovered to navigate the robot towards it. Simulation results highlighting the efficiency of the proposed scheme are presented.

Mobile robot trajectory planning for large volume data-muling from wireless sensor nodes

This article focuses on the utilization of a mobile robot as data mule for collecting and transferring data from a ground wireless sensor system (WSN). For the case, where the nodes communication is impeded either due to a non-connected node, or due to excessive retransmissions caused by significant packet losses, the effective transmission rate is reduced and the energy consumption for the RF-communication increases. In this case, the mobile element/robot approaches the nodes and collects data with a reduced packet loss rate resulted from the use of the proposed technique. The devised algorithm is implemented in the operating system Contiki. Then, the mobile element transfers the stored data to the desired destination. In the adopted scenario, the mobile element assumes prior knowledge of the nodes locations and its trajectory is extracted by solving a combinatorial optimization problem that resembles that of Traveling Salesman Subset-tour Problem (TSSP). Furthermore, the system is capable of transferring large volumes of data between source nodes and destination one, taking into account: a) the reliable data transmission, b) the traveling distances between the static nodes, c) the visiting/service time at each node and, d) the energy consumption of the mobile robot. Finally, experimental studies indicate the efficiency in terms of reliable data transmission and transmission time among pairs of static and a mobile node. Subsequently, the effectiveness of the overall concept is validated by means of simulations.

Load frequency control for demand disturbance attenuation and transient response improvement for a single-area power plant

This article concerns the design of linear feedback controllers for the load frequency control loop of a single area power plant. The system is affected by unknown piecewise constant power load disturbances. The control objective is formulated as a robust regulation control problem relying on an augmented state-space description by an integrator applied on the frequency deviation error. The primary controller achieves pole clustering in a prespecified LMI region, while in the sequel it is further enhanced with disturbance attenuation properties. In any case, the power load disturbances are rejected due to the integrator, while the transient behavior is determined by tuning the control parameters through a trade-off between performance criteria and actuation authority. Extensive simulation results demonstrate the complexity aspects of the design procedure and highlight the efficiency of the proposed control schemes.

Dynamics and control of an Unmanned Aerial Vehicle employing a delta-manipulator

The development of a dynamic model for control purposes of an Unmanned Aerial Vehicle (UAV) carrying a delta-manipulator for force exertion is the subject of this article. The floating base of the manipulator due to its attachment to the UAV dictates the need to account for the transfer of the reaction force and torque vector from the manipulators base to the UAV, and in a reverse manner, the transfer of the translational and angular velocity and acceleration vector from the UAV to the manipulator. The nature of the closed-kinematic chain of the delta-manipulator necessitates its dynamics approximation by three single Degree of Freedom arms which are kinematically-constrained thru its moving platform. The controller for the arm relies on a computed-torque framework, while the UAVs PD-controller accounts for the instantaneous displacement of the manipulators center-of-gravity with respect to its aerodynamic point of pressure. Gazebo-based simulation studies are provided to demonstrate the effectiveness of the suggested control scheme.

Collaborative mapping and navigation for a mobile robot swarm

The collaborative navigation of a team of ground mobile robots in an unknown planar environment towards fixed stationary targets is the subject of this paper. Each mobile robot is equipped with a limited field of view limited-range finder and a magnetometer to infer its orientation. Each target location is known, and a switching objective function initially guarantees the individual robots exploration towards its target area and afterwards safely guides each robot towards its target. During the collective exploration, the robots exchange their maps in a collaborative manner. If a robot detects the target that is assigned to another robot, it communicates this information to the corresponding robot and continues to explore its target. The other robot rather than performing exploration towards its already discovered target, it attempts to join its map with that of the reporting robot. Simulation results that prove the efficiency of the proposed scheme are presented.