Parallel Monte Carlo Tree Search with Batched Rigid-body Simulations for Speeding up Long-Horizon Episodic Robot Planning

We propose a novel Parallel Monte Carlo tree search with Batched Simulations (PMBS) algorithm for accelerating long-horizon, episodic robotic planning tasks. Monte Carlo tree search (MCTS) is an effective heuristic search algorithm for solving episodic decision-making problems whose underlying search spaces are expansive. Leveraging a GPU-based large-scale simulator, PMBS introduces massive parallelism into MCTS for solving planning tasks through the batched execution of a large number of concurrent simulations, which allows for more efficient and accurate evaluations of the expected cost-to-go over large action spaces. When applied to the challenging manipulation tasks of object retrieval from clutter, PMBS achieves a speedup of over $30\times$ with an improved solution quality, in comparison to a serial MCTS implementation. We show that PMBS can be directly applied to real robot hardware with negligible sim-to-real differences. Supplementary material, including video, can be found at https://github.com/arc-l/pmbs.Comment: Accepted for IROS 202

EARL: Eye-on-Hand Reinforcement Learner for Dynamic Grasping with Active Pose Estimation

In this paper, we explore the dynamic grasping of moving objects through active pose tracking and reinforcement learning for hand-eye coordination systems. Most existing vision-based robotic grasping methods implicitly assume target objects are stationary or moving predictably. Performing grasping of unpredictably moving objects presents a unique set of challenges. For example, a pre-computed robust grasp can become unreachable or unstable as the target object moves, and motion planning must also be adaptive. In this work, we present a new approach, Eye-on-hAnd Reinforcement Learner (EARL), for enabling coupled Eye-on-Hand (EoH) robotic manipulation systems to perform real-time active pose tracking and dynamic grasping of novel objects without explicit motion prediction. EARL readily addresses many thorny issues in automated hand-eye coordination, including fast-tracking of 6D object pose from vision, learning control policy for a robotic arm to track a moving object while keeping the object in the camera's field of view, and performing dynamic grasping. We demonstrate the effectiveness of our approach in extensive experiments validated on multiple commercial robotic arms in both simulations and complex real-world tasks.Comment: Presented on IROS 2023 Corresponding author Siddarth Jai

Transformation Model With Constraints for High Accuracy of 2D-3D Building Registration in Aerial Imagery

This paper proposes a novel rigorous transformation model for 2D-3D registration to address the difficult problem of obtaining a sufficient number of well-distributed ground control points (GCPs) in urban areas with tall buildings. The proposed model applies two types of geometric constraints, co-planarity and perpendicularity, to the conventional photogrammetric collinearity model. Both types of geometric information are directly obtained from geometric building structures, with which the geometric constraints are automatically created and combined into the conventional transformation model. A test field located in downtown Denver, Colorado, is used to evaluate the accuracy and reliability of the proposed method. The comparison analysis of the accuracy achieved by the proposed method and the conventional method is conducted. Experimental results demonstrated that: (1) the theoretical accuracy of the solved registration parameters can reach 0.47 pixels, whereas the other methods reach only 1.23 and 1.09 pixels; (2) the RMS values of 2D-3D registration achieved by the proposed model are only two pixels along the x and y directions, much smaller than the RMS values of the conventional model, which are approximately 10 pixels along the x and y directions. These results demonstrate that the proposed method is able to significantly improve the accuracy of 2D-3D registration with much fewer GCPs in urban areas with tall buildings

FPGA-Based On-Board Geometric Calibration for Linear CCD Array Sensors

With increasing demands in real-time or near real-time remotely sensed imagery applications in such as military deployments, quick response to terrorist attacks and disaster rescue, the on-board geometric calibration problem has attracted the attention of many scientists in recent years. This paper presents an on-board geometric calibration method for linear CCD sensor arrays using FPGA chips. The proposed method mainly consists of four modules—Input Data, Coefficient Calculation, Adjustment Computation and Comparison—in which the parallel computations for building the observation equations and least squares adjustment, are implemented using FPGA chips, for which a decomposed matrix inversion method is presented. A Xilinx Virtex-7 FPGA VC707 chip is selected and the MOMS-2P data used for inflight geometric calibration from DLR (Köln, Germany), are employed for validation and analysis. The experimental results demonstrated that: (1) When the widths of floating-point data from 44-bit to 64-bit are adopted, the FPGA resources, including the utilizations of FF, LUT, memory LUT, I/O and DSP48, are consumed at a fast increasing rate; thus, a 50-bit data width is recommended for FPGA-based geometric calibration. (2) Increasing number of ground control points (GCPs) does not significantly consume the FPGA resources, six GCPs is therefore recommended for geometric calibration. (3) The FPGA-based geometric calibration can reach approximately 24 times faster speed than the PC-based one does. (4) The accuracy from the proposed FPGA-based method is almost similar to the one from the inflight calibration if the calibration model and GCPs number are the same

Caution, Students at Large

A black bundle of fur hurtled through the doorway of Elm Hall and darted down the hallway. Wild-eyed, a coed shrieked her way after the little animal. Screams echoed through the dormitory as other occupants discovered the object of the chase- a tiny skunk

On Board Georeferencing Using FPGA-Based Optimized Second Order Polynomial Equation

For real-time monitoring of natural disasters, such as fire, volcano, flood, landslide, and coastal inundation, highly-accurate georeferenced remotely sensed imagery is needed. Georeferenced imagery can be fused with geographic spatial data sets to provide geographic coordinates and positing for regions of interest. This paper proposes an on-board georeferencing method for remotely sensed imagery, which contains five modules: input data, coordinate transformation, bilinear interpolation, and output data. The experimental results demonstrate multiple benefits of the proposed method: (1) the computation speed using the proposed algorithm is 8 times faster than that using PC computer; (2) the resources of the field programmable gate array (FPGA) can meet the requirements of design. In the coordinate transformation scheme, 250,656 LUTs, 499,268 registers, and 388 DSP48s are used. Furthermore, 27,218 LUTs, 45,823 registers, 456 RAM/FIFO, and 267 DSP48s are used in the bilinear interpolation module; (3) the values of root mean square errors (RMSEs) are less than one pixel, and the other statistics, such as maximum error, minimum error, and mean error are less than one pixel; (4) the gray values of the georeferenced image when implemented using FPGA have the same accuracy as those implemented using MATLAB and Visual studio (C++), and have a very close accuracy implemented using ENVI software; and (5) the on-chip power consumption is 0.659W. Therefore, it can be concluded that the proposed georeferencing method implemented using FPGA with second-order polynomial model and bilinear interpolation algorithm can achieve real-time geographic referencing for remotely sensed imagery

Metabolic Pathways Involved in Carbon Dioxide Enhanced Heat Tolerance in Bermudagrass

Global climate changes involve elevated temperature and CO2 concentration, imposing significant impact on plant growth of various plant species. Elevated temperature exacerbates heat damages, but elevated CO2 has positive effects on promoting plant growth and heat tolerance. The objective of this study was to identify metabolic pathways affected by elevated CO2 conferring the improvement of heat tolerance in a C4 perennial grass species, bermudagrass (Cynodon dactylon Pers.). Plants were planted under either ambient CO2 concentration (400 μmol⋅mol-1) or elevated CO2 concentration (800 μmol⋅mol-1) and subjected to ambient temperature (30/25°C, day/night) or heat stress (45/40°C, day/night). Elevated CO2 concentration suppressed heat-induced damages and improved heat tolerance in bermudagrass. The enhanced heat tolerance under elevated CO2 was attributed to some important metabolic pathways during which proteins and metabolites were up-regulated, including light reaction (ATP synthase subunit and photosystem I reaction center subunit) and carbon fixation [(glyceraldehyde-3-phosphate dehydrogenase, GAPDH), fructose-bisphosphate aldolase, phosphoglycerate kinase, sedoheptulose-1,7-bisphosphatase and sugars) of photosynthesis, glycolysis (GAPDH, glucose, fructose, and galactose) and TCA cycle (pyruvic acid, malic acid and malate dehydrogenase) of respiration, amino acid metabolism (aspartic acid, methionine, threonine, isoleucine, lysine, valine, alanine, and isoleucine) as well as the GABA shunt (GABA, glutamic acid, alanine, proline and 5-oxoproline). The up-regulation of those metabolic processes by elevated CO2 could at least partially contribute to the improvement of heat tolerance in perennial grass species

Determinants of sensitivity of human T-cell leukemia CCRF-CEM cells to immucillin-H

Immucillin-H (BCX-1777, forodesine) is a transition state analogue and potent inhibitor of PNP that shows promise as a specific agent against activated human T-cells and T-cell leukemias. The immunosuppressive or antileukemic effects of Immucillin-H (ImmH) require co-administration with deoxyguanosine (dGuo) to attain therapeutic levels of intracellular dGTP. In this study we investigated the requirements for sensitivity and resistance to ImmH and dGuo. 3H-ImmH transport assays demonstrated that the equilibrative nucleoside transporters (ENT1 and ENT2) facilitated the uptake of ImmH in human leukemia CCRF-CEM cells whereas 3H-dGuo uptake was primarily dependent upon concentrative nucleoside transporters (CNTs). Analysis of lysates from an ImmH-resistant CCRF-CEM-AraC-8D cells demonstrated undetectable deoxycytidine kinase (dCK) activity, suggesting that dCK and not deoxyguanosine kinase (dGK) was the rate-limiting enzyme for phosphorylation of dGuo in these cells. Examination of ImmH cytotoxicity in a hypoxanthine-guanine phosphoribosyltransferase (HGPRT)-deficient cell line CCRF-CEM-AraC-8C, demonstrated enhanced sensitivity to low concentrations of ImmH and dGuo. RT-PCR and sequencing of HGPRT from the HGPRT-deficient CCRF-CEM-AraC-8C cells identified an Exon 8 deletion mutation in this enzyme. Thus these studies show that specific nucleoside transporters are required for ImmH cytotoxicity and predict that ImmH may be more cytotoxic to 6-thioguanine (6-TG) or 6-thiopurine-resistant leukemia cells caused by HGPRT deficiency

On-Board Detection and Matching of Feature Points

This paper presents a FPGA-based method for on-board detection and matching of the feature points. With the proposed method, a parallel processing model and a pipeline structure are presented to ensure a high frame rate at processing speed, but with a low power consumption. To save the FPGA resources and increase the processing speed, a model which combines the modified SURF detector and a BRIEF descriptor, is presented as well. Three pairs of images with different land coverages are used to evaluate the performance of FPGA-based implementation. The experiment results demonstrate that (1) when the image pairs with artificial features (such as buildings and roads), the performance of FPGA-based implementation is better than those image pairs with natural features (such as woods); (2) the proposed FPGA-based method is capable of ensuring the processing speed at a high frame rate, such as the speed of can achieve 304 fps under a 100 MHz clock frequency. The speedup of the proposed implementation is about 27 times higher than that when using the PC-based implementation