Collective flying robots show great potential in many diverse indoor applications. Their added robustness, parallel operation and redundancy has clear advantages over a single flying robot. However, flying within cluttered and unprepared indoor environments, even for a single flying robot, is extremely challenging. The main reason why collective flying robots have not yet been successful within indoor environments, is due to a combination of several challenges related to the size constraints placed on an indoor hovering platform, which directly limits the available energy, embedded sensing and processing capabilities of a flying robot. The energetic cost of flying, places limits on the flight endurance and practicality of a swarm of flying robots. The current spatial-coordination approaches implement methods that are either too computationally expensive, or impractical for real-world operation, within unknown and unprepared indoor environments. The goal of this thesis was to develop a practical methodology for enabling energy efficient, autonomous indoor flying robots capable of inter-robot spatial-coordination for unprepared indoor environments, without using external aids. In order to enable collective operation of indoor flying robots, several practical methodologies have been proposed and demonstrated. A generalised design strategy has been proposed to dimension a hovering platform for a specific flight endurance, payload capability and robustness criteria. The developed method can be used as a practical design tool for anyone working with hovering platforms. The dimensioning strategy has created a design, which is highly suitable for carrying the necessary sensing and processing required to enable the collective operation of indoor flying robots. A simple sensing and control strategy is proposed for enabling anti-drift control and obstacle avoidance behaviours on an indoor highly dynamic, hovering platform. The approach has enabled one of the first indoor hovering platforms that could achieve such a capability without using any external aids. For the collective operation of indoor flying robots to work in reality, the on-board energy needs to be managed efficiently and conserved in a way that allows a swarm of robots to be useful, extending beyond the individual 10-20 min flight time. A generalised energy model has been developed, allowing for the accurate estimation of the flight endurance and perching time of hovering platforms. The energy model can be used to optimise the battery selection process of a hovering platform, to obtain the highest possible endurance. This is the only model known that is able to predict any combination of flying endurance and perching times. Additionally, a method of attaching to the ceiling has been presented that allows a flying robot to conserve energy and have a stable birds-eye-view while performing static sensing tasks. By applying energy management techniques, through use of energy modelling and behaviours that reduce the flight time, the energetic cost of flying can be mitigated and the mission endurance can be extended over several hours, which is especially useful for collective operation. A new infrared ranging technique has been developed that allows for a high sensing performance, including long range (12 m), high-speed (1 kHz / # robots) and high resolution (better than 1.1 cm up to 6 m). A practical on-board sensing method using this technique, has been developed that can provide spatial-coordination between multiple robots in three dimensions. The developed approach allows for easily adaptation, to suit other robots and applications, depending on a specific sensing speed and coverage requirement. The developed sensor is the worlds first embedded 3-D relative positioning sensor that has the ability to enable inter-robot spatial-coordination in three dimensions, which is necessary for achieving goal-directed flight on highly dynamic flying robots. A practical autonomous flight control methodology has been demonstrated that can provide hovering platform stabilisation, 3-D obstacle avoidance and 3-D waypoint navigation, all using the 3-D relative positioning sensor. Goal-directed flight and collective deployment have been achieved using only the information from the 3-D relative positioning sensing. The developed methodologies within this thesis, has enabled for the first time, the collective operation of highly dynamic indoor flying robots, without using external aids.