Search NASA⌕ Search

SEARCH · Search NASA

Results for “biologically inspired robots”

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.

At least 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Holarchical Systems and Emotional Holons : Biologically-Inspired System Designs for Control of Autonomous Aerial Vehicles

The BEES (Bio-inspired Engineering for Exploration Systems) for Mars project at NASA Ames Research Center has the goal of developing bio-inspired flight control strategies to enable aerial explorers for Mars scientific investigations. This paper presents a summary of our ongoing research into biologically inspired system designs for control of unmanned autonomous aerial vehicle communities for Mars exploration. First, we present cooperative design considerations for robotic explorers based on the holarchical nature of biological systems and communities. Second, an outline of an architecture for cognitive decision making and control of individual robotic explorers is presented, modeled after the emotional nervous system of cognitive biological systems. Keywords: Holarchy, Biologically Inspired, Emotional UAV Flight Control

Ippolito, Corey↗
NASA NTRS2003

Bio-inspired Computing for Robots

Living creatures may provide algorithms to enable active sensing/control systems in robots. Active sensing could enable planetary rovers to feel their way in unknown environments. The surface of Jupiter's moon Europa consists of fractured ice over a liquid sea that may contain microbes similar to those on Earth. To explore such extreme environments, NASA needs robots that autonomously survive, navigate, and gather scientific data. They will be too far away for guidance from Earth. They must sense their environment and control their own movements to avoid obstacles or investigate a science opportunity. To meet this challenge, CICT's Information Technology Strategic Research (ITSR) Project is funding neurobiologists at NASA's Jet Propulsion Laboratory (JPL) and selected universities to search for biologically inspired algorithms that enable robust active sensing and control for exploratory robots. Sources for these algorithms are living creatures, including rats and electric fish.

Laufenberg, Larry↗
NASA NTRS1992

Robustness of a distributed neural network controller for locomotion in a hexapod robot

A distributed neural-network controller for locomotion, based on insect neurobiology, has been used to control a hexapod robot. How robust is this controller? Disabling any single sensor, effector, or central component did not prevent the robot from walking. Furthermore, statically stable gaits could be established using either sensor input or central connections. Thus, a complex interplay between central neural elements and sensor inputs is responsible for the robustness of the controller and its ability to generate a continuous range of gaits. These results suggest that biologically inspired neural-network controllers may be a robust method for robotic control.

Chiel, Hillel J.↗
NASA NTRS2007

Artificial Muscles Based on Electroactive Polymers as an Enabling Tool in Biomimetics

Evolution has resolved many of nature's challenges leading to working and lasting solutions that employ principles of physics, chemistry, mechanical engineering, materials science, and many other fields of science and engineering. Nature's inventions have always inspired human achievements leading to effective materials, structures, tools, mechanisms, processes, algorithms, methods, systems, and many other benefits. Some of the technologies that have emerged include artificial intelligence, artificial vision, and artificial muscles, where the latter is the moniker for electroactive polymers (EAPs). To take advantage of these materials and make them practical actuators, efforts are made worldwide to develop capabilities that are critical to the field infrastructure. Researchers are developing analytical model and comprehensive understanding of EAP materials response mechanism as well as effective processing and characterization techniques. The field is still in its emerging state and robust materials are still not readily available; however, in recent years, significant progress has been made and commercial products have already started to appear. In the current paper, the state-of-the-art and challenges to artificial muscles as well as their potential application to biomimetic mechanisms and devices are described and discussed.

electroactive polymers↗
NASA NTRS2009

Humanlike Robots - The Upcoming Revolution in Robotics

Humans have always sought to imitate the human appearance, functions and intelligence. Human-like robots, which for many years have been a science fiction, are increasingly becoming an engineering reality resulting from the many advances in biologically inspired technologies. These biomimetic technologies include artificial intelligence, artificial vision and hearing as well as artificial muscles, also known as electroactive polymers (EAP). Robots, such as the vacuum cleaner Rumba and the robotic lawnmower, that don't have human shape, are already finding growing use in homes worldwide. As opposed to other human-made machines and devices, this technology raises also various questions and concerns and they need to be addressed as the technology advances. These include the need to prevent accidents, deliberate harm, or their use in crime. In this paper the state-of-the-art of the ultimate goal of biomimetics, the development of humanlike robots, the potentials and the challenges are reviewed.

EAP↗
NASA NTRS2011

Compliant Tactile Sensors

Tactile sensors are currently being designed to sense interactions with human hands or pen-like interfaces. They are generally embedded in screens, keyboards, mousepads, and pushbuttons. However, they are not well fitted to sense interactions with all kinds of objects. A novel sensor was originally designed to investigate robotics manipulation where not only the contact with an object needs to be detected, but also where the object needs to be held and manipulated. This tactile sensor has been designed with features that allow it to sense a large variety of objects in human environments. The sensor is capable of detecting forces coming from any direction. As a result, this sensor delivers a force vector with three components. In contrast to most of the tactile sensors that are flat, this one sticks out from the surface so that it is likely to come in contact with objects. The sensor conforms to the object with which it interacts. This augments the contact's surface, consequently reducing the stress applied to the object. This feature makes the sensor ideal for grabbing objects and other applications that require compliance with objects. The operational range of the sensor allows it to operate well with objects found in peoples' daily life. The fabrication of this sensor is simple and inexpensive because of its compact mechanical configuration and reduced electronics. These features are convenient for mass production of individual sensors as well as dense arrays. The biologically inspired tactile sensor is sensitive to both normal and lateral forces, providing better feedback to the host robot about the object to be grabbed. It has a high sensitivity, enabling its use in manipulation fingers, which typically have low mechanical impedance in order to be very compliant. The construction of the sensor is simple, using inexpensive technologies like silicon rubber molding and standard stock electronics.

Torres-Jara, Eduardo R.↗
NASA NTRS2011

Clonal Selection Based Artificial Immune System for Generalized Pattern Recognition

The last two decades has seen a rapid increase in the application of AIS (Artificial Immune Systems) modeled after the human immune system to a wide range of areas including network intrusion detection, job shop scheduling, classification, pattern recognition, and robot control. JPL (Jet Propulsion Laboratory) has developed an integrated pattern recognition/classification system called AISLE (Artificial Immune System for Learning and Exploration) based on biologically inspired models of B-cell dynamics in the immune system. When used for unsupervised or supervised classification, the method scales linearly with the number of dimensions, has performance that is relatively independent of the total size of the dataset, and has been shown to perform as well as traditional clustering methods. When used for pattern recognition, the method efficiently isolates the appropriate matches in the data set. The paper presents the underlying structure of AISLE and the results from a number of experimental studies.

pattern recognition↗
NASA NTRS2004

Bioinspired Engineering of Exploration Systems (BEES) - its Impact on Future Missions

This paper describes an overview of our "Bioinspired Engineering of Exploration Systems for Mars" ( "BEES for Mars") project. The BEES approach distills selected biologically inspired strategies utilizing motion cues/optic flow, bioinspired pattern recognition, biological visual and neural control systems, bioinspired sensing and communication techniques, and birds of prey inspired search and track algorithmic systems. Unique capabilities so enabled, provide potential solutions to future autonomous robotic space and planetary mission applications. With the first series of tests performed in September 2003, August 2004 and September 2004, we have demonstrated the BEES technologies at the El Mirage Dry Lakebed site in the Mojave Desert using Delta Wing experimental prototypes. We call these test flyers the "BEES flyer", since we are developing them as dedicated test platform for the newly developed bioinspired sensors, processors and algorithmic strategies. The Delta Wing offers a robust airframe that can sustain high G launches and offers ease of compact stowability and packaging along with scaling to small size and low ReynOld's number performance for a potential Mars deployment. Our approach to developing light weight, low power autonomous flight systems using concepts distilled from biology promises to enable new applications, of dual use to NASA and DoD needs. Small in size (0.5 -5 Kg) BEES Flyers are demonstrating capabilities for autonomous flight and sensor operability in Mars analog conditions. The BEES project team spans JPL, NASA Ames, Australian National University (ANU), Brigham Young University(BYU), DC Berkeiey, Analogic Computers Inc. and other institutions. The highlights from our recent flight demonstrations exhibiting new Mission enabling capabilities are described. Further, this paper describes two classes of potential new missions for Mars exploration: (1) the long range exploration missions, and (2) observation missions, for real time imaging of critical ephemeral phenomena, that can be enabled by use of BEES flyers. For example, such flyers can serve as a powerful black-box for critical descent and landing data and enablers for improved science missions complementing and supplementing the existing assets like landers and rovers by providing valuable exploration and quick extended low-altitude aerial coverage of the sites of interest by imaging them and distributing instruments to them. Imaging done by orbiters allows broad surface coverage at limited spatial resolution. Low altitude air-borne exploration of Mars offers a means for imaging large areas, perhaps up to several hundred kilometers, quickly and efficiently, providing a close-up birds-eye view of the planetary terrain and close-up approach to constrained difficult areas like canyons and craters. A novel approach to low-mass yet highly capable flyers is enabled by small aircraft equipped using sensors and processors and algorithms developed using BEES technology. This project is focused towards showing the direct impact of blending the best of artificial intelligence attributes and bioinspiration to create a leap beyond existing capability for our future Missions.

navigation↗
NASA NTRS2017

Methods and Apparatus for Autonomous Robotic Control

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on "stovepiped," or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.

Versace, Massimiliano↗
NASA NTRS2018

Methods and Apparatus for Autonomous Robotic Control

Sensory processing of visual, auditory, and other sensor information (e.g., visual imagery, LIDAR, RADAR) is conventionally based on "stovepiped," or isolated processing, with little interactions between modules. Biological systems, on the other hand, fuse multi-sensory information to identify nearby objects of interest more quickly, more efficiently, and with higher signal-to-noise ratios. Similarly, examples of the OpenSense technology disclosed herein use neurally inspired processing to identify and locate objects in a robot's environment. This enables the robot to navigate its environment more quickly and with lower computational and power requirements.

Versace, Massimiliano↗
NASA NTRS2014

Design and Control of Compliant Tensegrity Robots Through Simulation and Hardware Validation

To better understand the role of tensegrity structures in biological systems and their application to robotics, the Dynamic Tensegrity Robotics Lab at NASA Ames Research Center has developed and validated two different software environments for the analysis, simulation, and design of tensegrity robots. These tools, along with new control methodologies and the modular hardware components developed to validate them, are presented as a system for the design of actuated tensegrity structures. As evidenced from their appearance in many biological systems, tensegrity ("tensile-integrity") structures have unique physical properties which make them ideal for interaction with uncertain environments. Yet these characteristics, such as variable structural compliance, and global multi-path load distribution through the tension network, make design and control of bio-inspired tensegrity robots extremely challenging. This work presents the progress in using these two tools in tackling the design and control challenges. The results of this analysis includes multiple novel control approaches for mobility and terrain interaction of spherical tensegrity structures. The current hardware prototype of a six-bar tensegrity, code-named ReCTeR, is presented in the context of this validation.

Robotics↗
NASA NTRS2009

NASA Tech Briefs, August 2009

Topics covered include: Aligning a Receiving Antenna Array to Reduce Interference; Collecting Ground Samples for Balloon-Borne Instruments; Tethered Pyrotechnic Apparatus for Acquiring a Ground Sample; Enhanced Video-Oculography System; Joint Carrier-Phase Synchronization and LDPC Decoding; Dual-Polarization, Sideband-Separating, Balanced Receiver for 1.5 THz Modular Battery Charge Controller; Efficient Multiplexer FPGA Block Structures Based on G4FETs; VLSI Microsystem for Rapid Bioinformatic Pattern Recognition; Low-Noise Amplifier for 100 to 180 GHz; Improved Fabrication of Ceramic Matrix Composite/Foam Core Integrated Structures; Inert Welding/Brazing Gas Filters and Dryers; Fabricating Copper Nanotubes by Electrodeposition; Reducing Aerodynamic Drag on Empty Open Cargo Vehicles; Rotary Percussive Auto-Gopher for Deep Drilling and Sampling; More About Reconfigurable Exploratory Robotic Vehicles; Thermostatic Valves Containing Silicone-Oil Actuators; Improving Heat Flux Performance of Flat Surface in Spray-Cooling Systems; Treating Fibrous Insulation to Reduce Thermal Conductivity; Silica-Aerogel Composites Opacified with La(sub0.7)Sr(sub0.3)MnO3; Cyclic Oxidation Behavior of CuCrAl Cold-Sprayed Coatings for Reusable Launch Vehicles; Ceramic Fiber Structures for Cryogenic Load-Bearing Applications; Elastomer Reinforced with Carbon Nanotubes; Biologically Inspired Purification and Dispersion of SWCNTs; A Technique for Adjusting Eigenfrequencies of WGM Resonators; Low-Pressure, Field-Ionizing Mass Spectrometer; Modifying Operating Cycles to Increase Stability in a LITS; Chamber for Simulating Martian and Terrestrial Environments; Algorithm for Detecting a Bright Spot in an Image; Extreme Programming: Maestro Style; Adaptive Behavior for Mobile Robots; Protocol for Communication Networking for Formation Flying; Planning Complex Sequences Using Compressed Representations; and Self-Supervised Learning of Terrain Traversability from Proprioceptive Sensors.

Source record↗
NASA NTRS2005

Engineering Ultimate Self-Protection in Autonomic Agents for Space Exploration Missions

NASA's Exploration Initiative (EI) will push space exploration missions to the limit. Future missions will be required to be self-managing as well as self-directed, in order to meet the challenges of human and robotic space exploration. We discuss security and self protection in autonomic agent based-systems, and propose the ultimate self-protection mechanism for such systems-self-destruction. Like other metaphors in Autonomic Computing, this is inspired by biological systems, and is the analog of biological apoptosis. Finally, we discus the role it might play in future NASA space exploration missions.

Sterritt, Roy↗
NASA NTRS2013

Surface Navigation Using Optimized Waypoints and Particle Swarm Optimization

The design priority for manned space exploration missions is almost always placed on human safety. Proposed manned surface exploration tasks (lunar, asteroid sample returns, Mars) have the possibility of astronauts traveling several kilometers away from a home base. Deviations from preplanned paths are expected while exploring. In a time-critical emergency situation, there is a need to develop an optimal home base return path. The return path may or may not be similar to the outbound path, and what defines optimal may change with, and even within, each mission. A novel path planning algorithm and prototype program was developed using biologically inspired particle swarm optimization (PSO) that generates an optimal path of traversal while avoiding obstacles. Applications include emergency path planning on lunar, Martian, and/or asteroid surfaces, generating multiple scenarios for outbound missions, Earth-based search and rescue, as well as human manual traversal and/or path integration into robotic control systems. The strategy allows for a changing environment, and can be re-tasked at will and run in real-time situations. Given a random extraterrestrial planetary or small body surface position, the goal was to find the fastest (or shortest) path to an arbitrary position such as a safe zone or geographic objective, subject to possibly varying constraints. The problem requires a workable solution 100% of the time, though it does not require the absolute theoretical optimum. Obstacles should be avoided, but if they cannot be, then the algorithm needs to be smart enough to recognize this and deal with it. With some modifications, it works with non-stationary error topologies as well.

Birge, Brian↗
NASA NTRS2002

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↗
NASA NTRS2005

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↗