No abstract

No abstract

The operation of UAV swarms has attracted great attention as their coordination and cooperation could bring significant impact in both military and civilian applications. Despite this potential, there are key challenges to be addressed to enable UAV swarm operations. Unlike operations of a small number of aerial vehicles, the onboard decision‐making responsibility may be more favorably distributed across the UAV swarm taking into account their scalability and sustainability. This chapter addresses three main issues of UAV technologies enabling onboard decision‐making: task allocation, communication network connectivity, and guidance and control in UAV swarm operations. Moreover, state‐of‐the‐art propositions to solve these issues and their limitations are discussed. This chapter also emphasizes the need for a new decision‐making paradigm for more efficient and effective UAV swarm operations and shows its future direction.

Mobility as a Service (MaaS) is the integrated and on-demand offering of new mode-sharing transport schemes, such as ride-share, car-share or car-pooling. MaaS schemes may solve some of the most pressing mobility problems in large conurbations like London. However, MaaS schemes pose significant implementation challenges for operators and city authorities alike. With the existing transport and traffic planning tools, even basic questions do not have easy answers: e.g. how many vehicles are needed; how should they be deployed; what infrastructure changes are needed, and what will happen with congestion? This paper reports on the novel integration, through co-simulation of two independent agent-based simulators: MATSim and IMSim. MATSim generates realistic transport demand for a city: allocating travellers to the best mobility option according to their preferences; while IMSim provides a highly realistic operational execution of autonomous and manually driven transport fleets. We show how the simulation tools complement each other to deliver a superior Autonomous Mobility on Demand (AMoD) modelling capability. By combining the two, we can evaluate the impact of diverse AMoD scenarios from different standpoints: from a traveller's perspective (e.g. satisfaction, service level, etc.); from an operator's perspectives (e.g. cost, revenue, etc.); and from a city's perspective (e.g. congestion, significant shifts between transport modes, etc.). The coupled simulation methods have underpinned the extensive MERGE Greenwich project investigation into the challenges of offering ride-share services in autonomous vehicles in the Royal Borough of Greenwich (London, UK) for travellers, service-operators, the city, and vehicle manufacturers.

No abstract

This paper addresses the task allocation problem for multi-robot systems. The main issue with the task allocation problem is inherent complexity that makes finding an optimal solution within a reasonable time almost impossible. To hand the issue, this paper develops a task allocation algorithm that can be decentralised by leveraging the submodularity concepts and sampling process. The theoretical analysis reveals that the proposed algorithm can provide approximation guarantee of 1/2 for the monotone submodular case and 1/4 for the non-monotone submodular case in average sense with polynomial time complexity. To examine the performance of the proposed algorithm and validate the theoretical analysis results, we design a task allocation problem and perform numerical simulations. The simulation results confirm that the proposed algorithm achieves solution quality, which is comparable to a state-of-the-art algorithm in the monotone case, and much better quality in the non-monotone case with significantly less computational complexity.

This paper introduces a new strategy to improve the performance and reliability of multi-rotor vehicles. The strategy uses a dual axes tilting propeller in order to generate control actions. The mechanisms of actuation are: gyroscopic torques, thrust vectoring and differential thrusting. A realisation of the new concept is detailed in this paper. The model of the actuators is also described, including the rigid body equations of the propellers and the motors and servomotors dynamic response. A conventional control system is presented implementing a PD and a pseudoinverse control allocator to stabilise the vehicle. The tests show that the vehicle is faster than a conventional counterpart and that it can resist the failure of two rotors. The results suggest that higher inertia propellers can lead to further substantial improvements in performance.