Bruce Randall Donald

Kinodynamic motion planning

Kinodynamic planning attempts to solve a robot motion problem subject to simultaneous kinematic and dynamics constraints. In the general problem, given a robot system, we must find a minimal-time trajectory that goes from a start position and velocity to a goal position and velocity while avoiding obstacles by a safety margin and respecting constraints on velocity and acceleration. We consider the simplified case of a point mass under Newtonian mechanics, together with velocity and acceleration bounds. The point must be flown from a start to a goal, amidst polyhedral obstacles in 2D or 3D. Although exact solutions to this problem are not known, we provide the first provably good approximation algorithm, and show that it runs in polynomial time

Real-time robot motion planning using rasterizing computer graphics hardware

We present a real-time robot motion planner that is fast and complete to a resolution. The technique is guaranteed to find a path if one exists at the resolution, and all paths returned are safe. The planner can handle any polyhedral geometry of robot and obstacles, including disjoint and highly concave unions of polyhedra.The planner uses standard graphics hardware to rasterize configuration space obstacles into a series of bitmap slices, and then uses dynamic programming to create a navigation function (a discrete vector-valued function) and to calculate paths in this rasterized space. The motion paths which the planner produces are minimal with respect to an L1 (Manhattan) distance metric that includes rotation as well as translation.Several examples are shown illustrating the competence of the planner at generating planar rotational and translational plans for complex two and three dimensional robots. Dynamic motion sequences, including complicated and non-obvious backtracking solutions, can be executed in real time.

An untethered, electrostatic, globally controllable MEMS micro-robot

We present an untethered, electrostatic, MEMS micro-robot, with dimensions of 60 /spl mu/m by 250 /spl mu/m by 10 /spl mu/m. The device consists of a curved, cantilevered steering arm, mounted on an untethered scratch drive actuator (USDA). These two components are fabricated monolithically from the same sheet of conductive polysilicon, and receive a common power and control signal through a capacitive coupling with an underlying electrical grid. All locations on the grid receive the same power and control signal, so that the devices can be operated without knowledge of their position on the substrate. Individual control of the component actuators provides two distinct motion gaits (forward motion and turning), which together allow full coverage of a planar workspace. These MEMS micro-robots demonstrate turning error of less than 3.7/spl deg//mm during forward motion, turn with radii as small as 176 /spl mu/m, and achieve speeds of over 200 /spl mu/m/sec with an average step size as small as 12 nm. They have been shown to operate open-loop for distances exceeding 35 cm without failure, and can be controlled through teleoperation to navigate complex paths. The devices were fabricated through a multiuser surface micromachining process, and were postprocessed to add a patterned layer of tensile chromium, which curls the steering arms upward. After sacrificial release, the devices were transferred with a vacuum microprobe to the electrical grid for testing. This grid consists of a silicon substrate coated with 13-/spl mu/m microfabricated electrodes, arranged in an interdigitated fashion with 2-/spl mu/m spaces. The electrodes are insulated by a layer of electron-beam-evaporated zirconium dioxide, so that devices placed on top of the electrodes will experience an electrostatic force in response to an applied voltage. Control waveforms are broadcast to the device through the capacitive power coupling, and are decoded by the electromechanical response of the device body. Hysteresis in the system allows on-board storage of n=2 bits of state information in response to these electrical signals. The presence of on-board state information within the device itself allows each of the two device subsystems (USDA and steering arm) to be individually addressed and controlled. We describe this communication and control strategy and show necessary and sufficient conditions for voltage-selective actuation of all 2/sup n/ system states, both for our devices (n=2), and for the more general case (where n is larger.).

Moving furniture with teams of autonomous robots

The authors wish to organize furniture in a room with a team of robots that can push objects. The authors show how coordinated pushing by robots can change the pose (position and orientation) of objects and then they ask whether planning, global control, and explicit communication are necessary for cooperatively changing the pose of objects. The authors answer in the negative and present, as witnesses, four cooperative manipulation protocols that use different amounts of state, sensing, and communication. The authors analyze these protocols in the information invariant framework. The authors formalize the notion of resource tradeoffs for robot protocols and give the tradeoffs for the specific protocols discussed here.

Probabilistic Disease Classification of Expression-Dependent Proteomic Data from Mass Spectrometry of Human Serum

We have developed an algorithm called Q5 for probabilistic classification of healthy versus disease whole serum samples using mass spectrometry. The algorithm employs principal components analysis (PCA) followed by linear discriminant analysis (LDA) on whole spectrum surface-enhanced laser desorption/ionization time of flight (SELDI-TOF) mass spectrometry (MS) data and is demonstrated on four real datasets from complete, complex SELDI spectra of human blood serum. Q5 is a closed-form, exact solution to the problem of classification of complete mass spectra of a complex protein mixture. Q5 employs a probabilistic classification algorithm built upon a dimension-reduced linear discriminant analysis. Our solution is computationally efficient; it is noniterative and computes the optimal linear discriminant using closed-form equations. The optimal discriminant is computed and verified for datasets of complete, complex SELDI spectra of human blood serum. Replicate experiments of different training/testing splits of each dataset are employed to verify robustness of the algorithm. The probabilistic classification method achieves excellent performance. We achieve sensitivity, specificity, and positive predictive values above 97% on three ovarian cancer datasets and one prostate cancer dataset. The Q5 method outperforms previous full-spectrum complex sample spectral classification techniques and can provide clues as to the molecular identities of differentially expressed proteins and peptides.

Computational structure-based redesign of enzyme activity

We report a computational, structure-based redesign of the phenylalanine adenylation domain of the nonribosomal peptide synthetase enzyme gramicidin S synthetase A (GrsA-PheA) for a set of noncognate substrates for which the wild-type enzyme has little or virtually no specificity. Experimental validation of a set of top-ranked computationally predicted enzyme mutants shows significant improvement in the specificity for the target substrates. We further present enhancements to the methodology for computational enzyme redesign that are experimentally shown to result in significant additional improvements in the target substrate specificity. The mutant with the highest activity for a noncognate substrate exhibits 1/6 of the wild-type enzyme/wild-type substrate activity, further confirming the feasibility of our computational approach. Our results suggest that structure-based protein design can identify active mutants different from those selected by evolution.

Crystal structure, conformational fixation and entry-related interactions of mature ligand-free HIV-1 Env

As the sole viral antigen on the HIV-1–virion surface, trimeric Env is a focus of vaccine efforts. Here we present the structure of the ligand-free HIV-1–Env trimer, fix its conformation and determine its receptor interactions. Epitope analyses revealed trimeric ligand-free Env to be structurally compatible with broadly neutralizing antibodies but not poorly neutralizing ones. We coupled these compatibility considerations with binding antigenicity to engineer conformationally fixed Envs, including a 201C 433C (DS) variant specifically recognized by broadly neutralizing antibodies. DS-Env retained nanomolar affinity for the CD4 receptor, with which it formed an asymmetric intermediate: a closed trimer bound by a single CD4 without the typical antigenic hallmarks of CD4 induction. Antigenicity-guided structural design can thus be used both to delineate mechanism and to fix conformation, with DS-Env trimers in virus-like-particle and soluble formats providing a new generation of vaccine antigens.

Information invariants for distributed manipulation

In Donald (1995), we described a manipulation task for coop erating mobile robots that can push large, heavy objects. There, we asked whether explicit local and global communication between the agents can be removed from a family of pushing protocols. In this article, we answer in the affirmative. We do so by using the general methods of Donald (1995), analyzing information invariants. We discuss several measures for the information complexity of the task: (1) How much internal state should the robot retain? (2) How many cooperating agents are required, and how much communication between them is necessary? (3) How can the robot change (side effect) the environment to record state or sensory information for performing a task? (4) How much information is provided by sensors? and (5) How much computation is required by the robot? To answer these questions, we develop a notion of information invariants. We develop a technique whereby one sensor can be constructed from others by adding, deleting, and reallocating 1) through 5), among collaborating autonomous agents. We add a resource to measures 1) through 5) and ask: 6) How much information is provided by the task mechanics? By answering this question, we hope to develop information invariants that explicitly trade- off resource 6) with resources 1) through 5). The protocols we describe here have been implemented in several different forms, and we report on experiments to measure and analyze information invariants using a pair of cooperating mobile robots for manipulation experiments in our laboratory.

Planar Microassembly by Parallel Actuation of MEMS Microrobots

We present designs, theory, and results of fabrication and testing for a novel parallel microrobotic assembly scheme using stress-engineered MEMS microrobots. The robots are 240-280 mum times 60 mum times 7-20 mum in size and can be controlled to dock compliantly together, forming planar structures several times this size. The devices are classified into species based on the design of their steering arm actuators, and the species are further classified as independent if they can be maneuvered independently using a single global control signal. In this paper, we show that microrobot species are independent if the two transition voltages of their steering arms, i.e., the voltages at which the arms are raised or lowered, form a unique pair. We present control algorithms that can be applied to groups of independent microrobot species to direct their motion from arbitrary nondead-lock configurations to desired planar microassemblies. We present designs and fabrication for four independent microrobot species, each with a unique transition voltage. The fabricated microrobots are used to demonstrate directed assembly of five types of planar structures from two classes of initial conditions. We demonstrate an average docking accuracy of 5 mum and use self-aligning compliant interaction between the microrobots to further align and stabilize the intermediate assemblies. The final assemblies match their target shapes on average 96%, by area.

Enhanced Potency of a Broadly Neutralizing HIV-1 Antibody In Vitro Improves Protection against Lentiviral Infection In Vivo

ABSTRACT Over the past 5 years, a new generation of highly potent and broadly neutralizing HIV-1 antibodies has been identified. These antibodies can protect against lentiviral infection in nonhuman primates (NHPs), suggesting that passive antibody transfer would prevent HIV-1 transmission in humans. To increase the protective efficacy of such monoclonal antibodies, we employed next-generation sequencing, computational bioinformatics, and structure-guided design to enhance the neutralization potency and breadth of VRC01, an antibody that targets the CD4 binding site of the HIV-1 envelope. One variant, VRC07-523, was 5- to 8-fold more potent than VRC01, neutralized 96% of viruses tested, and displayed minimal autoreactivity. To compare its protective efficacy to that of VRC01 in vivo, we performed a series of simian-human immunodeficiency virus (SHIV) challenge experiments in nonhuman primates and calculated the doses of VRC07-523 and VRC01 that provide 50% protection (EC50). VRC07-523 prevented infection in NHPs at a 5-fold lower concentration than VRC01. These results suggest that increased neutralization potency in vitro correlates with improved protection against infection in vivo, documenting the improved functional efficacy of VRC07-523 and its potential clinical relevance for protecting against HIV-1 infection in humans. IMPORTANCE In the absence of an effective HIV-1 vaccine, alternative strategies are needed to block HIV-1 transmission. Direct administration of HIV-1-neutralizing antibodies may be able to prevent HIV-1 infections in humans. This approach could be especially useful in individuals at high risk for contracting HIV-1 and could be used together with antiretroviral drugs to prevent infection. To optimize the chance of success, such antibodies can be modified to improve their potency, breadth, and in vivo half-life. Here, knowledge of the structure of a potent neutralizing antibody, VRC01, that targets the CD4-binding site of the HIV-1 envelope protein was used to engineer a next-generation antibody with 5- to 8-fold increased potency in vitro. When administered to nonhuman primates, this antibody conferred protection at a 5-fold lower concentration than the original antibody. Our studies demonstrate an important correlation between in vitro assays used to evaluate the therapeutic potential of antibodies and their in vivo effectiveness.