Release of benzimidazole and benzylidene camphor from topical sunscreen formulations

Absorption of two ultraviolet (UV) filters was evaluated through a lipophilic synthetic membrane (Folioxane®) and excised hairless rat skin using a flow-through diffusion cell. Folioxane membrane is an artificial skin used in the treatment of third-degree burns. Diffusion tests were performed with aqueous solutions and galenic formulations (one water-in-oil [W/O] emulsion and two oily gels). Analyses were achieved with high-performance liquid chromatography (HPLC) with UV detection at 295 nm. Diffusion kinetics of 17 β estradiol, a reference compound, through rat skin, human skin, and Folioxane membrane were performed to validate the in vitro model. Phenylbenzimidazole and methylbenzylidene camphor in aqueous solutions were diffused at a regular rate through the Folioxane film. The release of phenylbenzimidazole was very slow, whereas the release of benzylidene camphor was more pronounced: a decrease of the quantity was observed in the donor compartment (30 % at 6 hr and 93% after 72 hr). A significant flow of benzylidene camphor was also measured through excised skin of rat in the first 3 hr. The skin absorption was 38% over 72 hr. The W/O emulsion had low penetration of UV filter: 20% of the initial amount for Folioxane membrane and 0.4% for rat skin. In contrast, the penetration of two oily gels was identical: 28% on Folioxane membrane and 0.6% on rat skin. This study demonstrates the transcutaneous diffusion of two important classes of sunscreens through a lipophilic Folioxane membrane and through excised hairless rat skin. From the results, Folioxane membrane appears to be an alternative model for studying diffusion of topical molecules and as a tool for guiding formulation choices.     

Dynamic optimization of N‐joint robotic limb deployments

We describe an approach using a stochastic optimization framework (SOF) for operating complex mobile systems with several degrees of freedom (DOFs), such as robotic limbs with N joints, in environments that can contain obstacles. As part of the SOF, we have employed an efficient simulated annealing algorithm normally used in computationally highly expensive optimization and search problems such as the traveling salesman problem and protein design. This algorithm is particularly suited to run onboard industrial robots, robots in telemedicine, remote spacecraft, planetary landers, and rovers, i.e., robotic platforms with limited computational capabilities. The robotic limb deployment optimization approach presented here offers an alternative to time‐intensive robotic arm deployment path planning algorithms in general and in particular for robotic limb systems in which closed‐form solutions do not exist. Application examples for a (N = 4)‐DOF arm on a planetary exploration rover are presented. © 2009 Wiley Periodicals, Inc.     

An Architecture for Distributed Environment Sensing with Application to Robotic Cliff Exploration

Future planetary exploration missions will use cooperative robots to explore and sample rough terrain. To succeed robots will need to cooperatively acquire and share data. Here a cooperative multi-agent sensing architecture is presented and applied to the mapping of a cliff surface. This algorithm efficiently repositions the systems' sensing agents using an information theoretic approach and fuses sensory information using physical models to yield a geometrically consistent environment map. This map is then distributed among the agents using an information based relevant data reduction scheme. Experimental results for cliff face mapping using the JPL Sample Return Rover (SRR) are presented. The method is shown to significantly improve mapping efficiency over conventional methods.     

Distributed Control of Multi-Robot Systems Engaged in Tightly Coupled Tasks

NASA mission concepts for the upcoming decades of this century include exploration of sites such as steep cliff faces on Mars, as well as infrastructure deployment for a sustained robotic/manned presence on planetary and/or the lunar surface. Single robotic platforms, such as the Sojourner rover successfully flown in 1997 and the Mars Exploration Rovers (MER) which landed on Mars in January of 2004, have neither the autonomy, mobility, nor manipulation capabilities for such ambitious undertakings. One possible approach to these future missions is the fielding of cooperative multi-robot systems that have the required onboard control algorithms to more or less autonomously perform tightly coordinated tasks. These control algorithms must operate under the constrained mass, volume, processing, and communication conditions that are present on NASA planetary surface rover systems. In this paper, we describe the design and implementation of distributed control algorithms that build on our earlier development of an enabling architecture called CAMPOUT (Control Architecture for Multi-robot Planetary Outposts). We also report on some ongoing physical experiments in tightly coupled distributed control at the Jet Propulsion Lab in Pasadena, CA where in the first study two rovers acquire and carry an extended payload over uneven, natural terrain, and in the second three rovers form a team for cliff access.     

Sustainable cooperative robotic technologies for human and robotic outpost infrastructure construction and maintenance

Robotic Construction Crew (RCC) is a heterogeneous multi-robot system for autonomous acquisition, transport, and precision mating of components in construction tasks. RCC minimizes use of resources constrained by a space environment such as computation, power, communication, and sensing. A behavior-based architecture provides adaptability and robustness despite low computational requirements. RCC successfully performs several construction related tasks in an emulated outdoor environment despite high levels of uncertainty in motions and sensing. This paper provides quantitative results for formation keeping in component transport, precision instrument placement, and construction tasks.     

CAMPOUT: a control architecture for tightly coupled coordination of multirobot systems for planetary surface exploration

Exploration of high risk terrain areas such as cliff faces and site construction operations by autonomous robotic systems on Mars requires a control architecture that is able to autonomously adapt to uncertainties in knowledge of the environment. We report on the development of a software/hardware framework for cooperating multiple robots performing such tightly coordinated tasks. This work builds on our earlier research into autonomous planetary rovers and robot arms. Here, we seek to closely coordinate the mobility and manipulation of multiple robots to perform examples of a cliff traverse for science data acquisition, and site construction operations including grasping, hoisting, and transport of extended objects such as large array sensors over natural, unpredictable terrain. In support of this work we have developed an enabling distributed control architecture called control architecture for multirobot planetary outposts (CAMPOUT) wherein integrated multirobot mobility and control mechanisms are derived as group compositions and coordination of more basic behaviors under a task-level multiagent planner. CAMPOUT includes the necessary group behaviors and communication mechanisms for coordinated/cooperative control of heterogeneous robotic platforms. In this paper, we describe CAMPOUT, and its application to ongoing physical experiments with multirobot systems at the Jet Propulsion Laboratory in Pasadena, CA, for exploration of cliff faces and deployment of extended payloads.     

LEMUR: Legged Excursion Mechanical Utility Rover

Although future orbital facilities will have immense scale, details will require intricate operations in restrictive, confined quarters. LEMUR is a small, agile and capable six-legged walking robot that has been built at the Jet Propulsion Laboratory to perform dexterous small-scale assembly, inspection and maintenance. It is intended to expand the operational envelope of robots in its size class (sub-5 kg) through the flexible use of its limbs and effectors, as well as through the modular changeout of those effectors. In short, LEMUR is intended as a robotic instantiation of a six-limbed primate with Swiss Army knife tendencies.LEMUR's layout consists of six independently operated limbs arranged in two rows of three. The front two limbs have four active degrees of freedom while the rear four limbs have three each. Each limb is reconfigurable to allow the integration of a variety of mechanical tools.     

Computational Aspects of Cognition and Consciousness in Intelligent Devices

We review computational intelligence methods of sensory perception and cognitive functions in animals, humans, and artificial devices. Top-down symbolic methods and bottom-up sub-symbolic approaches are described. In recent years, computational intelligence, cognitive science and neuroscience have achieved a level of maturity that allows integration of top-down and bottom-up approaches in modeling the brain. Continuous adaptation and teaming is a key component of computationally intelligent devices, which is achieved using dynamic models of cognition and consciousness. Human cognition performs a granulation of the seemingly homogeneous temporal sequences of perceptual experiences into meaningful and comprehensible chunks of concepts and complex behavioral sehemas. They are accessed during action selection and conscious decision making as part of the intentional cognitive cycle. Implementations in computational and robotic environments are demonstrated.