A Retrospective of Project Robo Raven: Developing New Capabilities for Enhancing the Performance of Flapping Wing Aerial Vehicles.

Flapping Wing Air Vehicles (FWAVs) have proven to be attractive alternatives to fixed wing and rotary air vehicles at low speeds because of their bio-inspired ability to hover and maneuver. However, in the past, they have not been able to reach their full potential due to limitations in wing control and payload capacity, which also has limited endurance. Many previous FWAVs used a single actuator that couples and synchronizes motions of the wings to flap both wings, resulting in only variable rate flapping control at a constant amplitude. Independent wing control is achieved using two servo actuators that enable wing motions for FWAVs by programming positions and velocities to achieve desired wing shapes and associated aerodynamic forces. However, having two actuators integrated into the flying platform significantly increases its weight and makes it more challenging to achieve flight than a single actuator. This article presents a retrospective overview of five different designs from the "Robo Raven" family based on our previously published work. The first FWAVs utilize two servo motors to achieve independent wing control. The basic platform is capable of successfully performing dives, flips, and button hook turns, which demonstrates the potential maneuverability afforded by the independently actuated and controlled wings. Subsequent designs in the Robo Raven family were able to use multifunctional wings to harvest solar energy to overcome limitations on endurance, use on-board decision-making capabilities to perform maneuvers autonomously, and use mixed-mode propulsion to increase payload capacity by exploiting the benefits of fixed and flapping wing flight. This article elucidates how each successive version of the Robo Raven platform built upon the findings from previous generations. The Robo Raven family collectively addresses requirements related to control autonomy, energy autonomy, and maneuverability. We conclude this article by identifying new opportunities for research in avian-scale flapping wing aerial vehicles.

Area-Coverage Planning for Spray-based Surface Disinfection with a Mobile Manipulator.

The use of robots has significantly increased to fight highly contagious diseases like SARS-COV-2, Ebola, MERS, and others. One of the important applications of robots to fight such infectious diseases is disinfection. Manual disinfection can be a time-consuming, risky, labor-intensive, and mundane, and humans may fail to disinfect critical areas due to the resulting fatigue. Autonomous or semi-autonomous mobile manipulators mounted with a spray nozzle at the end-effector can be very effective in spraying disinfectant liquid for deep disinfection of objects and surfaces. In this paper, we present an area-coverage planning algorithm to compute a path that the nozzle follows to disinfect surfaces represented by their point clouds. We project the point cloud on a plane and produce a polygon on which we generate multiple spray paths using our branch and bound-based tree search area-coverage algorithm such that the spray paths cover the entire area of the polygon. An appropriate spray path is chosen using a robot capability map-based selection criterion. We generate mobile manipulator trajectories using successive refinement-based parametric optimization so that the paths for the nozzle are followed accurately. Thereafter, we need to make sure that the joint velocities of the mobile manipulator are regulated appropriately such that each point on the surface receives enough disinfectant spray. To this end, we compute the time intervals between the robot path waypoints such that enough disinfectant liquid is sprayed on all points of the point cloud that results in thorough disinfection of the surface, and the particular robot path is executed in the minimum possible time. We have implemented the area-coverage planning and mobile manipulator motion planning on five test scenarios in simulation using our ADAMMS-SD (Agile Dexterous Autonomous Mobile Manipulation System for Surface Disinfection) robot. We benchmark our spray path generation algorithm with three competing methods by showing that the generated paths are significantly more efficient in terms of area coverage and reducing disinfectant wastage. We also show the time interval computation between successive waypoints results in thorough disinfection of surfaces.

Assessing Industrial Robot agility through international competitions.

Manufacturing and Industrial Robotics have reached a point where to be more useful to small and medium sized manufacturers, the systems must become more agile and must be able to adapt to changes in the environment. This paper describes the process for creating and the lessons learned over multiple years of the Agile Robotics for Industrial Automation Competition (ARIAC) being run by the National Institute of Standards and Technology.

HANDLING PERCEPTION UNCERTAINTY IN SIMULATION BASED SINGULATION PLANNING FOR ROBOTIC BIN PICKING.

Robotic bin picking requires using a perception system to estimate the pose of the parts in the bin. The selected singulation plan should be robust with respect to perception uncertainties. If the estimated posture is significantly different from the actual posture, then the singulation plan may fail during execution. In such cases, the singulation process will need to be repeated. We are interested in selecting singulation plans that minimize the expected task completion time. In order to estimate the expected task completion time for a proposed singulation plan, we need to estimate the probability of success and the plan execution time. Robotic bin picking needs to be done in real-time. Therefore, candidate singulation plans need to be generated and evaluated in real-time. This paper presents an approach for utilizing computationally efficient simulations for generating singulation plans. Results from physical experiments match well with predictions obtained from simulations.

Multipass Target Search in Natural Environments.

Consider a disaster scenario where search and rescue workers must search difficult to access buildings during an earthquake or flood. Often, finding survivors a few hours sooner results in a dramatic increase in saved lives, suggesting the use of drones for expedient rescue operations. Entropy can be used to quantify the generation and resolution of uncertainty. When searching for targets, maximizing mutual information of future sensor observations will minimize expected target location uncertainty by minimizing the entropy of the future estimate. Motion planning for multi-target autonomous search requires planning over an area with an imperfect sensor and may require multiple passes, which is hindered by the submodularity property of mutual information. Further, mission duration constraints must be handled accordingly, requiring consideration of the vehicle's dynamics to generate feasible trajectories and must plan trajectories spanning the entire mission duration, something which most information gathering algorithms are incapable of doing. If unanticipated changes occur in an uncertain environment, new plans must be generated quickly. In addition, planning multipass trajectories requires evaluating path dependent rewards, requiring planning in the space of all previously selected actions, compounding the problem. We present an anytime algorithm for autonomous multipass target search in natural environments. The algorithm is capable of generating long duration dynamically feasible multipass coverage plans that maximize mutual information using a variety of techniques such as ϵ -admissible heuristics to speed up the search. To the authors' knowledge this is the first attempt at efficiently solving multipass target search problems of such long duration. The proposed algorithm is based on best first branch and bound and is benchmarked against state of the art algorithms adapted to the problem in natural Simplex environments, gathering the most information in the given search time.

Optical micromanipulation of active cells with minimal perturbations: direct and indirect pushing.

The challenge to wide application of optical tweezers in biological micromanipulation is the photodamage caused by high-intensity laser exposure to the manipulated living systems. While direct exposure to infrared lasers is less likely to kill cells, it can affect cell behavior and signaling. Pushing cells with optically trapped objects has been introduced as a less invasive alternative, but the technique includes some exposure of the biological object to parts of the optical tweezer beam. To keep the cells farther away from the laser, we introduce an indirect pushing-based technique for noninvasive manipulation of sensitive cells. We compare how cells respond to three manipulation approaches: direct manipulation, pushing, and indirect pushing. We find that indirect manipulation techniques lessen the impact of manipulation on cell behavior. Cell survival increases, as does the ability of cells to maintain shape and wiggle. Our experiments also demonstrate that indirect pushing allows cell-cell contacts to be formed in a controllable way, while retaining the ability of cells to change shape and move.

Significantly improved trapping lifetime of nanoparticles in an optical trap using feedback control.

We demonstrate an increase in trapping lifetime for optically trapped nanoparticles by more than an order of magnitude using feedback control, with no corresponding increase in beam power. Langevin dynamics simulations were used to design the control law, and this technique was then demonstrated experimentally using 100 nm gold particles and 350 nm silica particles. No particle escapes were detected with the controller on, leading to lower limits on the increase in lifetime for 100 nm gold particles of 26 times (at constant average beam power) and 22 times for 350 nm silica particles (with average beam power reduced by one-third). The approach described here can be combined with other techniques, such as counter propagating beams or higher-order optical modes, to trap the smallest nanoparticles and can be used to reduce optical heating of particles that are susceptible to photodamage, such as biological systems.

Survey on indirect optical manipulation of cells, nucleic acids, and motor proteins.

Optical tweezers have emerged as a promising technique for manipulating biological objects. Instead of direct laser exposure, more often than not, optically-trapped beads are attached to the ends or boundaries of the objects for translation, rotation, and stretching. This is referred to as indirect optical manipulation. In this paper, we utilize the concept of robotic gripping to explain the different experimental setups which are commonly used for indirect manipulation of cells, nucleic acids, and motor proteins. We also give an overview of the kind of biological insights provided by this technique. We conclude by highlighting the trends across the experimental studies, and discuss challenges and promising directions in this domain of active current research.

Design of Revolute Joints for In-Mold Assembly Using Insert Molding.

Creating highly articulated miniature structures requires assembling a large number of small parts. This is a very challenging task and increases cost of mechanical assemblies. Insert molding presents the possibility of creating a highly articulated structure in a single molding step. This can be accomplished by placing multiple metallic bearings in the mold and injecting plastic on top of them. In theory, this idea can generate a multi degree of freedom structures in just one processing step without requiring any post molding assembly operations. However, the polymer material has a tendency to shrink on top of the metal bearings and hence jam the joints. Hence, until now insert molding has not been used to create articulated structures. This paper presents a theoretical model for estimating the extent of joint jamming that occurs due to the shrinkage of the polymer on top of the metal bearings. The level of joint jamming is seen as the effective torque needed to overcome the friction in the revolute joints formed by insert molding. We then use this model to select the optimum design parameters which can be used to fabricate functional, highly articulating assemblies while meeting manufacturing constraints. Our analysis shows that the strength of weld-lines formed during the in-mold assembly process play a significant role in determining the minimum joint dimensions necessary for fabricating functional revolute joints. We have used the models and methods described in this paper to successfully fabricate the structure for a minimally invasive medical robot prototype with potential applications in neurosurgery. To the best of our knowledge, this is the first demonstration of building an articulated structure with multiple degrees of freedom using insert molding.

A survey of snake-inspired robot designs.

Body undulation used by snakes and the physical architecture of a snake body may offer significant benefits over typical legged or wheeled locomotion designs in certain types of scenarios. A large number of research groups have developed snake-inspired robots to exploit these benefits. The purpose of this review is to report different types of snake-inspired robot designs and categorize them based on their main characteristics. For each category, we discuss their relative advantages and disadvantages. This review will assist in familiarizing a newcomer to the field with the existing designs and their distinguishing features. We hope that by studying existing robots, future designers will be able to create new designs by adopting features from successful robots. The review also summarizes the design challenges associated with the further advancement of the field and deploying snake-inspired robots in practice.

Training mechanical engineering students to utilize biological inspiration during product development.

The use of bio-inspiration for the development of new products and devices requires new educational tools for students consisting of appropriate design and manufacturing technologies, as well as curriculum. At the University of Maryland, new educational tools have been developed that introduce bio-inspired product realization to undergraduate mechanical engineering students. These tools include the development of a bio-inspired design repository, a concurrent fabrication and assembly manufacturing technology, a series of undergraduate curriculum modules and a new senior elective in the bio-inspired robotics area. This paper first presents an overview of the two new design and manufacturing technologies that enable students to realize bio-inspired products, and describes how these technologies are integrated into the undergraduate educational experience. Then, the undergraduate curriculum modules are presented, which provide students with the fundamental design and manufacturing principles needed to support bio-inspired product and device development. Finally, an elective bio-inspired robotics project course is present, which provides undergraduates with the opportunity to demonstrate the application of the knowledge acquired through the curriculum modules in their senior year using the new design and manufacturing technologies.