Wings of flying animals can not only generate lift and control torques but also can sense their surroundings. Such dual functions of sensing and actuation coupled in one element are particularly useful for small sized bio-inspired robotic flyers, whose weight, size, and power are under stringent constraint. In this work, we present the first flapping-wing robot using its flapping wings for environmental perception and navigation in tight space, without the need for any visual feedback. As the test platform, we introduce the Purdu Hummingbird, a flapping-wing robot with 17cm wingspan and 12 grams weight, with a pair of 30-40Hz flapping wings driven by only two actuators. By interpreting the wing loading feedback and its variations, the vehicle can detect the presence of environmental changes such as grounds, walls, stairs, obstacles and wind gust. The instantaneous wing loading can be obtained through the measurements and interpretation of the current feedback by the motors that actuate the wings. The effectiveness of the proposed approach is experimentally demonstrated on several challenging flight tasks without vision: terrain following, wall following and going through a narrow corridor. To ensure flight stability, a robust controller was designed for handling unforeseen disturbances during the flight. Sensing and navigating one’s environment through actuator loading is a promising method for mobile robots, and it can serve as an alternative or complementary method to visual perception.
Besides visual perception, haptic feedback provides another method for environment sensing. Inspired by the cockroaches antennas, researchers implemented artificial antennas on ground vehicles for tactile sensing @cite_19 @cite_8 . They demonstrated successful wall detection and following without visual cues. Similarly, as presented in @cite_27 , the legged robot can use contact responses of the leg to leverage a Bayesian classifier for terrain identification. The touch sensing strategy can be used on the FWMAVs as well. In this paper, we achieve the same function without using any specialized sensors, only measuring wing loading to infer the surroundings change. By taking advantages of the flexibility and reciprocating motion of the flapping wing, the safety of the FWMAV can be assured if the wing collided. In comparison, rigid-winged vehicles usually avoid hitting objects to prevent the wing wear and tear, e.g., drones need a cage-like shield to ensure passive safety when traveling through tight spaces with obstacles and turns @cite_29 .
@cite_19 @cite_27 @cite_29 @cite_8
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Through the use of mechanical, actuated antennae a biologically-inspired robot is capable of autonomous decision-making and navigation when faced with an obstacle that can be climbed over or tunneled under. Vertically-sweeping mechanical antennae and interface microcontrollers have been added to the Whegs ™ II [1] sensor platform that allow it to autonomously sense the presence of, and successfully navigate a horizontal shelf placed in its path. The obstacle is sensed when the antennae make contact with it, and navigation is made possible through articulation of the Whegs ™ II body flexion joint. In this paper, we explore the idea of using inertial and actuator information to accurately identify the environment of an amphibious robot. In particular, in our work with a legged robot we use internal sensors to measure the dynamics and interaction forces experienced by the robot. From these measurements we use simple machine learning methods to probabilistically infer properties of the environment, and therefore identify it. The robot’s gait can then be automatically selected in response to environmental changes. Experimental results show that for several environments (sand, water, snow, ice, etc.), the identification process is over 90 per cent accurate. The requisite data can be collected during a half-leg rotation (about 250 ms), making it one of the fastest and most economical environment identifiers for a dynamic robot. For the littoral setting, a gaitchange experiment is done as a proof-of-concept of a robot automatically adapting its gait to suit the environment. On 7 February 2015 in Dubai, United Arab Emirates (UAE), with applause from an international jury of drone experts, UAE ministers, and international dignitaries, His Highness Mohammed bin Rashid Al Maktoum handed us a US$1 million check and the first-place prize of the UAE Drones for Good Award, the “World Cup of drones.”