TY - JOUR
T1 - Bioinspired engineering of exploration systems
T2 - A horizon sensor/attitude reference system based on the dragonfly ocelli for Mars exploration applications
AU - Chahl, Javaan
AU - Thakoor, Sarita
AU - Le Bouffant, Naig
AU - Stange, Gert
AU - Srinivasan, M. V.
AU - Hine, Butler
AU - Zornetzer, Steven
PY - 2003/1
Y1 - 2003/1
N2 - Bioinspired engineering of exploration systems (BEES) is a fast emerging new discipline. It focuses on distilling the principles found in successful, nature-tested mechanisms of specific crucial functions that are hard to accomplish by conventional methods, but are accomplished rather deftly in nature by biological organisms. The intent is not just to mimic operational mechanisms found in a specific biological organism but to imbibe the salient principles from a variety of diverse organisms for the desired crucial function. Thereby, we can build exploration systems that have specific capabilities endowed beyond nature, as they will possess a mix of the best nature-tested mechanisms for each particular function. Insects (for example, honey bees and dragonflies) cope remarkably well with their world, despite possessing a brain that carries less than 0.01% as many neurons as ours does. Although most insects have immobile eyes, fixed focus optics, and lack stereo vision, they use a number of ingenious strategies for perceiving their world in three dimensions and navigating successfully in it. We are distilling some of these insect-inspired strategies for utilizing optical cues to obtain unique solutions to navigation, hazard avoidance, altitude hold, stable flight, terrain following, and smooth deployment of payload. Such functionality can enable access to otherwise unreachable exploration sites for much sought-after data. A BEES approach to developing autonomous flight systems, particularly in small scale, can thus have a tremendous impact on autonomous airborne navigation of these biomorphic flyers particularly for planetary exploration missions, for example, to Mars which offer unique challenges due to its thin atmosphere, low gravity, and lack of magnetic field. Incorporating these success strategies of bioinspired navigation into biomorphic sensors such as the horizon sensor described herein fulfills for the first time the requirements of a variety of potential future Mars exploration applications described in this paper. Specifically we have obtained lightweight (∼6 g), low power (<40 mW), and robust autonomous horizon sensing for flight stabilization based on distilling the principles of the dragonfly ocelli. Such levels of miniaturization of navigation sensors are essential to enable biomorphic microflyers (<1 kg) that can be deployed in large numbers for distributed measurements. In this paper we present the first experimental test results of a biomorphic flyer platform with an embedded biomorphic ocellus (the dragonfly-inspired horizon sensor/attitude reference system). These results from the novel hardware implementation of a horizon sensor demonstrate the advantage of our approach in adapting principles proven successful in nature to accomplish navigation for Mars exploration.
AB - Bioinspired engineering of exploration systems (BEES) is a fast emerging new discipline. It focuses on distilling the principles found in successful, nature-tested mechanisms of specific crucial functions that are hard to accomplish by conventional methods, but are accomplished rather deftly in nature by biological organisms. The intent is not just to mimic operational mechanisms found in a specific biological organism but to imbibe the salient principles from a variety of diverse organisms for the desired crucial function. Thereby, we can build exploration systems that have specific capabilities endowed beyond nature, as they will possess a mix of the best nature-tested mechanisms for each particular function. Insects (for example, honey bees and dragonflies) cope remarkably well with their world, despite possessing a brain that carries less than 0.01% as many neurons as ours does. Although most insects have immobile eyes, fixed focus optics, and lack stereo vision, they use a number of ingenious strategies for perceiving their world in three dimensions and navigating successfully in it. We are distilling some of these insect-inspired strategies for utilizing optical cues to obtain unique solutions to navigation, hazard avoidance, altitude hold, stable flight, terrain following, and smooth deployment of payload. Such functionality can enable access to otherwise unreachable exploration sites for much sought-after data. A BEES approach to developing autonomous flight systems, particularly in small scale, can thus have a tremendous impact on autonomous airborne navigation of these biomorphic flyers particularly for planetary exploration missions, for example, to Mars which offer unique challenges due to its thin atmosphere, low gravity, and lack of magnetic field. Incorporating these success strategies of bioinspired navigation into biomorphic sensors such as the horizon sensor described herein fulfills for the first time the requirements of a variety of potential future Mars exploration applications described in this paper. Specifically we have obtained lightweight (∼6 g), low power (<40 mW), and robust autonomous horizon sensing for flight stabilization based on distilling the principles of the dragonfly ocelli. Such levels of miniaturization of navigation sensors are essential to enable biomorphic microflyers (<1 kg) that can be deployed in large numbers for distributed measurements. In this paper we present the first experimental test results of a biomorphic flyer platform with an embedded biomorphic ocellus (the dragonfly-inspired horizon sensor/attitude reference system). These results from the novel hardware implementation of a horizon sensor demonstrate the advantage of our approach in adapting principles proven successful in nature to accomplish navigation for Mars exploration.
UR - http://www.scopus.com/inward/record.url?scp=0037232517&partnerID=8YFLogxK
U2 - 10.1002/rob.10068
DO - 10.1002/rob.10068
M3 - Article
SN - 0741-2223
VL - 20
SP - 35
EP - 42
JO - Journal of Robotic Systems
JF - Journal of Robotic Systems
IS - 1
ER -