Bioinspired engineering of exploration systems for NASA and DoD

A new approach called bioinspired engineering of exploration systems (BEES) and its value for solving pressing NASA and DoD needs are described. Insects (for example honeybees and dragonflies) cope remarkably well with their world, despite possessing a brain containing less than 0.01% as many neurons as the human brain. Although most insects have immobile eyes with fixed focus optics and lack stereo vision, they use a number of ingenious, computationally simple strategies for perceiving their world in three dimensions and navigating successfully within it. We are distilling selected insect-inspired strategies to obtain novel solutions for navigation, hazard avoidance, altitude hold, stable flight, terrain following, and gentle deployment of payload. Such functionality provides potential solutions for future autonomous robotic space and planetary explorers. A BEES approach to developing lightweight low-power autonomous flight systems should be useful for flight control of such biomorphic flyers for both NASA and DoD needs. Recent biological studies of mammalian retinas confirm that representations of multiple features of the visual world are systematically parsed and processed in parallel. Features are mapped to a stack of cellular strata within the retina. Each of these representations can be efficiently modeled in semiconductor cellular nonlinear network (CNN) chips. We describe recent breakthroughs in exploring the feasibility of the unique blending of insect strategies of navigation with mammalian visual search, pattern recognition, and image understanding into hybrid biomorphic flyers for future planetary and terrestrial applications. We describe a few future mission scenarios for Mars exploration, uniquely enabled by these newly developed biomorphic flyers

Aquatic escape for micro-aerial vehicles

As our world is experiencing climate changes, we are in need of better monitoring technologies. Most of our planet is covered with water and robots will need to move in aquatic environments. A mobile robotic platform that possesses efficient locomotion and is capable of operating in diverse scenarios would give us an advantage in data collection that can validate climate models, emergency relief and experimental biological research. This field of application is the driving vector of this robotics research which aims to understand, produce and demonstrate solutions of aerial-aquatic autonomous vehicles. However, small robots face major challenges in operating both in water and in air, as well as transition between those fluids, mainly due to the difference of density of the media. This thesis presents the developments of new aquatic locomotion strategies at small scales that further enlarge the operational domain of conventional platforms. This comprises flight, shallow water locomotion and the transition in-between. Their operating principles, manufacturing methods and control methods are discussed and evaluated in detail. I present multiple unique aerial-aquatic robots with various water escape mechanisms, spanning over different scales. The five robotic platforms showcased share similarities that are compared. The take-off methods are analysed carefully and the underlying physics principles put into light. While all presented research fulfils a similar locomotion objective - i.e aerial and aquatic motion - their relevance depends on the environmental conditions and supposed mission. As such, the performance of each vehicle is discussed and characterised in real, relevant conditions. A novel water-reactive fuel thruster is developed for impulsive take-off, allowing consecutive and multiple jump-gliding from the water surface in rough conditions. At a smaller scale, the escape of a milligram robotic bee is achieved. In addition, a new robot class is demonstrated, that employs the same wings for flying as for passive surface sailing. This unique capability allows the flexibility of flight to be combined with long-duration surface missions, enabling autonomous prolonged aquatic monitoring.Open Acces

NeBula: Team CoSTAR's robotic autonomy solution that won phase II of DARPA Subterranean Challenge

This paper presents and discusses algorithms, hardware, and software architecture developed by the TEAM CoSTAR (Collaborative SubTerranean Autonomous Robots), competing in the DARPA Subterranean Challenge. Specifically, it presents the techniques utilized within the Tunnel (2019) and Urban (2020) competitions, where CoSTAR achieved second and first place, respectively. We also discuss CoSTAR¿s demonstrations in Martian-analog surface and subsurface (lava tubes) exploration. The paper introduces our autonomy solution, referred to as NeBula (Networked Belief-aware Perceptual Autonomy). NeBula is an uncertainty-aware framework that aims at enabling resilient and modular autonomy solutions by performing reasoning and decision making in the belief space (space of probability distributions over the robot and world states). We discuss various components of the NeBula framework, including (i) geometric and semantic environment mapping, (ii) a multi-modal positioning system, (iii) traversability analysis and local planning, (iv) global motion planning and exploration behavior, (v) risk-aware mission planning, (vi) networking and decentralized reasoning, and (vii) learning-enabled adaptation. We discuss the performance of NeBula on several robot types (e.g., wheeled, legged, flying), in various environments. We discuss the specific results and lessons learned from fielding this solution in the challenging courses of the DARPA Subterranean Challenge competition.The work is partially supported by the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004), and Defense Advanced Research Projects Agency (DARPA)

Insect inspired visual motion sensing and flying robots

International audienceFlying insects excellently master visual motion sensing techniques. They use dedicated motion processing circuits at a low energy and computational costs. Thanks to observations obtained on insect visual guidance, we developed visual motion sensors and bio-inspired autopilots dedicated to flying robots. Optic flow-based visuomotor control systems have been implemented on an increasingly large number of sighted autonomous robots. In this chapter, we present how we designed and constructed local motion sensors and how we implemented bio-inspired visual guidance scheme on-board several micro-aerial vehicles. An hyperacurate sensor in which retinal micro-scanning movements are performed via a small piezo-bender actuator was mounted onto a miniature aerial robot. The OSCAR II robot is able to track a moving target accurately by exploiting the microscan-ning movement imposed to its eye's retina. We also present two interdependent control schemes driving the eye in robot angular position and the robot's body angular position with respect to a visual target but without any knowledge of the robot's orientation in the global frame. This "steering-by-gazing" control strategy, which is implemented on this lightweight (100 g) miniature sighted aerial robot, demonstrates the effectiveness of this biomimetic visual/inertial heading control strategy

RoboBat: dynamics and control of flapping flight micro aerial vehicles

Flapping flight micro aerial vehicles (MAVs) are of interest to the aerospace and robotics communities for their maneuverability in comparison to tradition fixed wing and rotary aircraft. However they present numerous challenges in the fields of dynamics, stability and control. This thesis examines the dynamics and kinematics of robotic flapping flight, the design and construction of a robotic bat test bed mounted on a 3-DOF pendulum, and subsequent control experiments using the test bed. The robotic bat test bed is capable of exhibiting different wing motions and is used to test the feasibility of controlling the motions of the robotic bat by using the phase differences between coupled nonlinear oscillators called central pattern generators (CPGs). A dynamic model for the robotic bat based on the complex wing kinematics is presented, and the wing kinematic motions themselves are analyzed using a high-speed motion capture system. Mechanical coupling effects which deviate from theoretical assumptions are investigated as well. Open loop experiments analyzing the steady state behavior of the bat's flight with varying phase differences showed a change of the pitch angle while elevation and forward velocity remains constant. Closed loop experiments indeed validate that control dimension reduction is achievable by controlling the phase differences of CPG oscillators. Unstable longitudinal modes are stabilized and controlled using only control of two parameters: phase difference and flapping frequency. Transition between flapping flight and gliding flight is analyzed. This shows promising results regarding the relation between phase differences of wing motions and longitudinal stability, and lays the groundwork for future research and experimentation in flapping flight MAVs