Megha Gupta

Using manipulation primitives for brick sorting in clutter

This paper explores the idea of manipulation-aided perception and grasping in the context of sorting small objects on a tabletop. We present a robust pipeline that combines perception and manipulation to accurately sort Duplo bricks by color and size. The pipeline uses two simple motion primitives to manipulate the scene in ways that help the robot to improve its perception. This results in the ability to sort cluttered piles of Duplo bricks accurately. We present experimental results on the PR2 robot comparing brick sorting without the aid of manipulation to sorting with manipulation primitives that show the benefits of the latter, particularly as the degree of clutter in the environment increases.

Using Manipulation Primitives for Object Sorting in Cluttered Environments

This paper explores the idea of manipulation-aided perception and grasping in the context of sorting small objects on a cluttered tabletop. We present a robust pipeline that combines perception and manipulation to accurately sort objects by some property (e.g., color, size, shape, etc.). The pipeline uses two motion primitives to manipulate the scene in ways that help the robot to improve its perception and grasps. This results in the ability to sort cluttered object piles accurately. We also present an implementation on the PR2 robot that applies our algorithm to sort Duplo bricks by color and size, and compare our method to brick sorting without the aid of manipulation. The experimental results demonstrate the benefits of our approach, particularly in environments with a high degree of clutter.

Interactive environment exploration in clutter

Robotic environment exploration in cluttered environments is a challenging problem. The number and variety of objects present not only make perception very difficult but also introduce many constraints for robot navigation and manipulation. In this paper, we investigate the idea of exploring a small, bounded environment (e.g., the shelf of a home refrigerator) by prehensile and non-prehensile manipulation of the objects it contains. The presence of multiple objects results in partial and occluded views of the scene. This inherent uncertainty in the scenes state forces the robot to adopt an observe-plan-act strategy and interleave planning with execution. Objects occupying the space and potentially occluding other hidden objects are rearranged to reveal more of the unseen area. The environment is considered explored when the state (free or occupied) of every voxel in the volume is known. The presented algorithm can be easily adapted to real world problems like object search, taking inventory, and mapping. We evaluate our planner in simulation using various metrics like planning time, number of actions required, and length of planning horizon. We then present an implementation on the PR2 robot and use it for object search in clutter.

Quantitative Contour Analysis as an Image-based Discriminator Between Benign and Malignant Renal Tumors

OBJECTIVE To investigate whether morphologic analysis can differentiate between benign and malignant renal tumors on clinically acquired imaging. MATERIALS AND METHODS Between 2009 and 2014, 3-dimensional tumor volumes were manually segmented from contrast-enhanced computerized tomography (CT) images from 150 patients with predominantly solid, nonmacroscopic fat-containing renal tumors: 100 renal cell carcinomas and 50 benign lesions (eg, oncocytoma and lipid-poor angiomyolipoma). Tessellated 3-dimensional tumor models were created from segmented voxels using MATLAB code. Eleven shape descriptors were calculated: sphericity, compactness, mean radial distance, standard deviation of the radial distance, radial distance area ratio, zero crossing, entropy, Feret ratio, convex hull area and convex hull perimeter ratios, and elliptic compactness. Morphometric parameters were compared using the Wilcoxon rank-sum test to investigate whether malignant renal masses demonstrate more morphologic irregularity than benign ones. RESULTS Only CHP in sagittal orientation (median 0.96 vs 0.97) and EC in coronal orientation (median 0.92 vs 0.93) differed significantly between malignant and benign masses (P = .04). When comparing these 2 metrics between coronal and sagittal orientations, similar but nonsignificant trends emerged (P = .07). Other metrics tested were not significantly different in any imaging plane. CONCLUSION Computerized image analysis is feasible using shape descriptors that otherwise cannot be visually assessed and used without quantification. Shape analysis via the transverse orientation may be reasonable, but encompassing all 3 planar dimensions to characterize tumor contour can achieve a more comprehensive evaluation. Two shape metrics (CHP and EC) may help distinguish benign from malignant renal tumors, an often challenging goal to achieve on imaging and biopsy.

A scheduling and routing algorithm for digital microfluidic ring layouts with bus-phase addressing

Digital microfluidic systems (DMFS) are a new class of lab-on-a-chip systems for biochemical analysis. A DMFS uses electro wetting to manipulate discrete droplets on a planar array of electrodes. The chemical analysis is performed by repeatedly moving, mixing, and splitting droplets on the electrodes. Recently, there has been a lot of interest in developing algorithms and computational tools for the design, simulation, and performance evaluation of DMFS. In this paper, we present an algorithm for coordinating droplet movement in batch mode operations on ring layouts with bus-phase addressing. In bus- phase systems, each electrode is not individually addressable, instead a set of electrodes are all controlled by the same signal. Though this hardware design simplifies chip fabrication, it increases the complexity of routing droplets. The presented algorithm allows multiple independent reactions, each with two reactants and one product, and chain reactions with multiple stages, where each stage produces reactants for the next stage, to take place simultaneously on the chip. This algorithm is scalable to different number of reactions within a limit which depends on the size of the layout, placement of sources and number of phases used. It also addresses any sensor constraints under which droplets need to visit sensor locations for specified amounts of time. We present simulation results using our algorithm to coordinate droplet movements for example analyses on a ring layout.

Interactive Segmentation of Textured and Textureless Objects

This article describes interactive object segmentation for autonomous service robots acting in human living environments. The proposed system allows a robot to effectively segment textured and textureless objects in cluttered scenes by leveraging its manipulation capabilities. In this interactive perception approach, RGB and depth (RGB-D) camera based features are tracked while the robot actively induces motions into a scene using its arm. The robot autonomously infers appropriate arm movements which can effectively separate objects. The resulting tracked feature trajectories are assigned to their corresponding object by clustering. In the final step, we reconstruct the dense models of the objects from the previously clustered sparse RGB-D features. The approach is integrated with robotic grasping and is demonstrated on scenes consisting of various textured and textureless objects, showing the advantages of a tight integration between perception, cognition and action.

Collective transport of robots: Coherent, minimalist multi-robot leader-following

We study the collective transport of robots (CTR) problem. A large number of commodity mobile robots are to be moved from one location to another by a single operator. Joysticking each one or carrying them physically is impractical. None of the robots are particularly sophisticated in their ability to plan or reason. Prior work on flocking and formation control has addressed the transport of a robot group that maintains its integrity by explicitly controlling coherence. We show how flocking emerges as a consequence of each robot contending for space near the human operator. A coherent flock can be made to follow a leader in this manner thereby solving the CTR problem. We also present the design of a hand-worn IMU-based gesture interface which allows the human operator to issue simple commands to the group. A preliminary experimental evaluation of the system shows robust CTR with different leader behaviors.