Energetics in robotic flight at small scales

Abstract

Recent advances in design, sensing and control have led to aerial robots that offer great promise in a range of real-world applications. However, one critical open question centres on how to improve the energetic efficiency of aerial robots so that they can be useful in practical situations. This review paper provides a survey on small-scale aerial robots (i.e. less than 1 m 2 area foot print, and less than 3 kg weight) from the point of view of energetics. The paper discusses methods to improve the efficiency of aerial vehicles, and reports on recent findings by the authors and other groups on modelling the impact of aerodynamics for the purpose of building energy-aware motion planners and controllers.

Fast, autonomous flight in GPS‐denied and cluttered environments

“…In recent times, there has been an explosion of research on microaerial vehicles (MAVs), ranging from low‐level control (Lee, Leok, & McClamroch, ) to high‐level, specification‐based planning (Wolff, Topcu, & Murray, ). One class of MAVs, the quadrotor, has become popular in academia and industry alike due to its mechanical and control simplicity, high maneuverability, and low cost of entry point compared to other aerial robots (Karydis & Kumar, ). Indeed, there have been numerous applications of quadrotors to fields such as intelligence, surveillance and reconnaissance, aerial photography, structural inspection (Özaslan et al., ), robotic first responders (Mohta et al., ), and cooperative construction (Augugliaro et al., ) and aerial manipulation (Thomas, Loianno, Polin, Sreenath, & Kumar, ).…”

UAV Payload Transportation via RTDP Based Optimized Velocity Profiles

“…A paper by [15] showed that energy consumption increases with forward velocity after a first decrease, when compared to the energy consumption in a hover condition. Another study by [16] evaluated the direct relation between energy efficiency and the speed of a multi-rotor system.…”

“…The total thrust required to stay airborne would be T = mg (cos θ cos φ) . If the yaw angle is fixed to zero and T from the above equation is substituted in equations of motion, the multi-rotor equations of motion can be reduced to Equations (14) and (15).…”

The Influence of Limited Visual Sensing on the Reynolds Flocking Algorithm

“…Recent advances in the field of aerial robotics and sensor technologies have greatly enhanced the capabilities of unmanned aerial vehicles (UAVs). One consequence of this outcome has been the growing interest in multi-aerial vehicle applications [1], [2], [3]. Clear benefits of multi-drone systems are envisioned for a wide range of missions including search and rescue [4], long-term monitoring [5], sensor data collection [6], indoor navigation [7], environment exploration [8] and cooperative grasping and transportation [9].…”