Indoor real-time localisation for multiple autonomous vehicles fusing vision, odometry and IMU data

Due to the increasing usage of service and industrial autonomous vehicles, a precise localisation is an essential component required in many applications, e.g. indoor robot navigation. In open outdoor environments, differential GPS systems can provide precise positioning information. However, there are many applications in which GPS cannot be used, such as indoor environments. In this work, we aim to increase robot autonomy providing a localisation system based on passive markers, that fuses three kinds of data through extended Kalman filters. With the use of low cost devices, the optical data are combined with other robots’ sensor signals, i.e. odometry and inertial measurement units (IMU) data, in order to obtain accurate localisation at higher tracking frequencies. The entire system has been developed fully integrated with the Robotic Operating System (ROS) and has been validated with real robots

Coordination of unmanned marine vehicles for asymmetric threats protection

A coordination protocol for systems of unmanned marine vehicles is proposed for protection against asymmetric threats. The problem is first mod- elled in a game theoretic framework, as a potential game. Then an extension of existing learning algo- rithms is proposed to address the problem of tracking the possibly moving threat. The approach is evaluated in scenarios of different geometric complexity such as open sea, bay, and harbours. Performance of the approach is evaluated in terms of a security index that will allow us to obtain a tool for team sizing. The tool provides the minimum number of marine vehicles to be used in the system, given a desired security level to be guaranteed and the maximum threat velocity

Assessing the potential of autonomous multi-agent surveillance in asset protection from underwater threats

A Serious Game (SG) system for the assessment of the potential of the multi-vehicle surveillance is presented. The SG system is applied to the problem of protection of strategic assets from underwater asymmetric threats. The SG platform integrates the active sonar performance evaluator able to estimate the real performance on the basis of the environmental conditions. The final goal is to provide new technology tools to realize a Decision Support System (DDS) to support the design phase of a naval unit. The SG system is developed in the framework of the ProDifCon project supported by the (DLTM) (Italy)

Motion primitive based random planning for loco-manipulation tasks

Several advanced control laws are available for complex robotic systems such as humanoid robots and mobile manipulators. Controls are usually developed for locomotion or for manipulation purposes. Resulting motions are usually executed sequentially and the potentiality of the robotic platform is not fully exploited. In this work we consider the problem of loco-manipulation planning for a robot with given parametrized control laws known as primitives. Such primitives, may have not been designed to be executed simultaneously and by composing them instability may easily arise. With the proposed approach, primitives combination that guarantee stability of the system are obtained resulting in complex whole-body behavior. A formal definition of motion primitives is provided and a random sampling approach on a manifold with limited dimension is investigated. Probabilistic completeness and asymptotic optimality are also proved. The proposed approach is tested both on a mobile manipulator and on the humanoid robot Walk-Man, performing loco-manipulation tasks

Variable stiffness control for oscillation damping

In this paper a model-free approach for damping control of Variable Stiffness Actuators is proposed. The idea is to take advantage of the possibility to change the stiffness of the actuators in controlling the damping. The problem of minimizing the terminal energy for a one degree of freedom spring-mass model with controlled stiffness is first considered. The optimal bang-bang control law uses a maximum stiffness when the link gets away from the desired position, i.e. the link velocity is decreasing, and a minimum one when the link is going towards it, i.e. the link velocity is increasing. Based on Lyapunov stability theorems the obtained law has been proved to be stable for a multi-DoF system. Finally, the proposed control law has been tested and validated through experimental tests

Distributed motion misbehavior detection in teams of heterogeneous aerial robots

This paper addresses the problem of detecting possible misbehavior in a group of autonomous mobile robots, which coexist in a shared environment and interact with each other and coordinate according to a set of common interaction rules. Such rules specify what actions each robot is allowed to perform in order to interact with the other members of the group. The rules are distributed, i.e., they can be evaluated only starting from the knowledge of the individual robot and the information the robot gathers from neighboring robots. We consider misbehaving those robots which, because of either spontaneous failures or malicious tampering, do not follow the rules and whose behavior thus deviates from the nominal assigned one. The main contribution of the paper is to provide a methodology to detect such misbehavior by observing the congruence of actual behavior with the assigned rules as applied to the actual state of the system. The presented methodology is based on a consensus protocol on the events observed by robots. The methodology is fully distributed in the sense that it can be performed by individual robots based only on the local available information, it has been theoretically proven and validated with experiments involving real aerial heterogeneous robots