Flying STAR2, a Hybrid Flying Driving Robot with a Clutch Mechanism and Energy Optimization Algorithm - Gefen, Eran; Zarrouk, David (IEEE access, 2022)
This paper presents FSTAR2, an improved FSTAR design, and a near optimal energy-based algorithm for a flying-driving robot that can navigate in environments crowded with obstacles. The robot can be used for tasks such as package deliveries, industrial inspection, and search and rescue applications. FSTAR2 is fitted with a clutch mechanism that separates the propellers from the motors when driving. Experiments show that the clutch reduces the driving energy consumption by up to 52% and enables driving at higher speeds. To optimize its energy consumption (reducing its normalized energy cost) the FSTAR2 exploits its flying and driving capabilities by implementing a new approach which encloses the search space of the weighted A* algorithm and finds a new weight for the heuristic function, yielding a near optimal solution. Given that both flying and driving speeds are subject to environmental restrictions, the algorithm favors driving whenever possible (driving is almost three times more energy efficient at the considered speed - 2 m/s). Multiple simulations in different environments were conducted and the findings were compared to Dijkstra's algorithm to estimate the quality of the results. In general, the weighted A* algorithm reduced the number of iterations vs the A* algorithm and produced very similar values to Dijkstra's Algorithm. The experimental robot can fly like a regular drone, penetrate (25 cm/10 inches diameter) pipes and drive at speeds of up to 4.5 m/s, which is an increase of 50% compared to FSTAR.