Search NASA⌕ Search

SEARCH · Search NASA

Results for “biomorphic robotics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

Biomorphic Systems and Biomorphic Missions

A viewgraph presentation (with an explanation for each slide) gives an overview of biomorphic systems and missions. Biomorphic explorers are classified, and the challenge to obtain a biomorphic robot is described. Characteristics of biomorphic explorers are described, and biomorphic missions are discussed.

Sarita Thakoor↗

Biomorphic Explorers Leading Towards a Robotic Ecology

This paper presents viewgraphs of biomorphic explorers as they provide extended survival and useful life of robots in ecology. The topics include: 1) Biomorphic Explorers; 2) Advanced Mobility for Biomorphic Explorers; 3) Biomorphic Explorers: Size Based Classification; 4) Biomorphic Explorers: Classification (Based on Mobility and Ambient Environment); 5) Biomorphic Flight Systems: Vision; 6) Biomorphic Glider Deployment Concept: Larger Glider Deploy/Local Relay; 7) Biomorphic Glider Deployment Concept: Balloon Deploy/Dual Relay; 8) Biomorphic Exlplorer: Conceptual Design; 9) Biomorphic Gliders; and 10) Applications.

Thakoor, Sarita↗

Insect-Inspired Flight Control for Unmanned Aerial Vehicles

Flight-control and navigation systems inspired by the structure and function of the visual system and brain of insects have been proposed for a class of developmental miniature robotic aircraft called "biomorphic flyers" described earlier in "Development of Biomorphic Flyers" (NPO-30554), NASA Tech Briefs, Vol. 28, No. 11 (November 2004), page 54. These form a subset of biomorphic explorers, which, as reported in several articles in past issues of NASA Tech Briefs ["Biomorphic Explorers" (NPO-20142), Vol. 22, No. 9 (September 1998), page 71; "Bio-Inspired Engineering of Exploration Systems" (NPO-21142), Vol. 27, No. 5 (May 2003), page 54; and "Cooperative Lander-Surface/Aerial Microflyer Missions for Mars Exploration" (NPO-30286), Vol. 28, No. 5 (May 2004), page 36], are proposed small robots, equipped with microsensors and communication systems, that would incorporate crucial functions of mobility, adaptability, and even cooperative behavior. These functions are inherent to biological organisms but are challenging frontiers for technical systems. Biomorphic flyers could be used on Earth or remote planets to explore otherwise difficult or impossible to reach sites. An example of an exploratory task of search/surveillance functions currently being tested is to obtain high-resolution aerial imagery, using a variety of miniaturized electronic cameras. The control functions to be implemented by the systems in development include holding altitude, avoiding hazards, following terrain, navigation by reference to recognizable terrain features, stabilization of flight, and smooth landing. Flying insects perform these and other functions remarkably well, even though insect brains contains fewer than 10(exp -4) as many neurons as does the human brain. Although most insects have immobile, fixed-focus eyes and lack stereoscopy (and hence cannot perceive depth directly), they utilize a number of ingenious strategies for perceiving, and navigating in, three dimensions. Despite their lack of stereoscopy, insects infer distances to potential obstacles and other objects from image motion cues that result from their own motions in the environment. The concept of motion of texture in images as a source of motion cues is denoted generally as the concept of optic or optical flow. Computationally, a strategy based on optical flow is simpler than is stereoscopy for avoiding hazards and following terrain. Hence, this strategy offers the potential to design vision-based control computing subsystems that would be more compact, would weigh less, and would demand less power than would subsystems of equivalent capability based on a conventional stereoscopic approach.

Thakoor, Sarita↗

Improved Autoassociative Neural Networks

Improved autoassociative neural networks, denoted nexi, have been proposed for use in controlling autonomous robots, including mobile exploratory robots of the biomorphic type. In comparison with conventional autoassociative neural networks, nexi would be more complex but more capable in that they could be trained to do more complex tasks. A nexus would use bit weights and simple arithmetic in a manner that would enable training and operation without a central processing unit, programs, weight registers, or large amounts of memory. Only a relatively small amount of memory (to hold the bit weights) and a simple logic application- specific integrated circuit would be needed. A description of autoassociative neural networks is prerequisite to a meaningful description of a nexus. An autoassociative network is a set of neurons that are completely connected in the sense that each neuron receives input from, and sends output to, all the other neurons. (In some instantiations, a neuron could also send output back to its own input terminal.) The state of a neuron is completely determined by the inner product of its inputs with weights associated with its input channel. Setting the weights sets the behavior of the network. The neurons of an autoassociative network are usually regarded as comprising a row or vector. Time is a quantized phenomenon for most autoassociative networks in the sense that time proceeds in discrete steps. At each time step, the row of neurons forms a pattern: some neurons are firing, some are not. Hence, the current state of an autoassociative network can be described with a single binary vector. As time goes by, the network changes the vector. Autoassociative networks move vectors over hyperspace landscapes of possibilities.

Hand, Charles↗

NASA Tech Briefs, November 2004

Topics include: Multifunction Imaging and Spectroscopic Instrument; Position-Finding Instrument Built Around a Magnetometer; Improved Measurement of Dispersion in an Optical Fiber; Probe for Sampling of Interstitial Fluid From Bone; Neuropsychological Testing of Astronauts; Method of Calibration for a Large Cathetometer System; Four-Channel PC/104 MIL-STD-1553 Circuit Board; Improved Method of Locating Defects in Wiring Insulation; Strobe Traffic Lights Warn of Approaching Emergency Vehicles; Improved Timing Scheme for Spaceborne Precipitation Radar; Concept for Multiple-Access Free-Space Laser Communications; Variable Shadow Screens for Imaging Optical Devices; Verifying Diagnostic Software; Initial Processing of Infrared Spectral Data; Activity-Centric Approach to Distributed Programming; Controlling Distributed Planning; New Material for Surface-Enhanced Raman Spectroscopy; Treated Carbon Nanofibers for Storing Energy in Aqueous KOH; Advanced Infant Car Seat Would Increase Highway Safety; Development of Biomorphic Flyers; Second-Generation Six-Limbed Experimental Robot; Miniature Linear Actuator for Small Spacecraft; Process for Making Single-Domain Magnetite Crystals; A New Process for Fabricating Random Silicon Nanotips; Resin-Transfer-Molding of a Tool Face; Improved Phase-Mask Fabrication of Fiber Bragg Gratings; Tool for Insertion of a Fiber-Optic Terminus in a Connector; Nanofluidic Size-Exclusion Chromatograph; Lightweight, Low-CTE Tubes Made From Biaxially Oriented LCPs; Using Redundancy To Reduce Errors in Magnetometer Readings; Compact Instrument for Measuring Profile of a Light Beam; Multilayer Dielectric Transmissive Optical Phase Modulator; Second-Generation Multi-Angle Imaging Spectroradiometer; Real-Time Adaptive Color Segmentation by Neural Networks; Research and Development in Optical Communications; Tests of Multibeam Scintillation Mitigation on Laser Uplinks; and Spaceborne Infrared Atmospheric Sounder.

Source record↗

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.

Space Flight↗