Lawson L. S. Wong

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We consider the problem of grasping novel objects in cluttered environments. If a full 3-d model of the scene were available, one could use the model to estimate the stability and robustness of different grasps (formalized as form/force-closure, etc); in practice, however, a robot facing a novel object will usually be able to perceive only the front(More)
— Object search is an integral part of daily life, and in the quest for competent mobile manipulation robots it is an unavoidable problem. Previous approaches focus on cases where objects are in unknown rooms but lying out in the open, which transforms object search into active visual search. However, in real life, objects may be in the back of cupboards(More)
We present our vision-based system for grasping novel objects in cluttered environments. Our system can be divided into four components: 1) decide where to grasp an object, 2) perceive obstacles, 3) plan an obstacle-free path, and 4) follow the path to grasp the object. While most prior work assumes availability of a detailed 3-d model of the environment,(More)
In this paper, we describe our methodologies and empirical evaluations for the shot boundary detection and automatic video search tasks at TRECVID 2006. For the shot boundary detection task, we consider a simple and efficient solution. Our approach first applies adaptive thresholding on color histogram differences between frames to select candidates for(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract— In state estimation, we often want the maximum likelihood estimate of the current state. For the commonly used joint multivariate Gaussian distribution over the state space, this can be efficiently found using a Kalman filter.(More)
Autonomous mobile-manipulation robots need to sense and interact with objects to accomplish high-level tasks such as preparing meals and searching for objects. To achieve such tasks, robots need semantic world models, defined as object-based representations of the world involving task-level attributes. In this work, we address the problem of estimating(More)
The MIT Faculty has made this article openly available. Please share how this access benefits you. Your story matters. Abstract— Spatial representations are fundamental to mobile robots operating in uncertain environments. Two frequently-used representations are occupancy grid maps, which only model metric information, and object-based world models, which(More)
Fig. 1. Given a tabletop scene (top), we want to estimate the types and poses of objects in the scene using a black-box object detector. From a single Kinect RGB-D image, however, objects may be occluded or erroneously classified. The bottom left depicts a rendered image, with detections superimposed in red; three objects are missing due to occlusion, and(More)
Autonomous mobile-manipulation robots need to sense and interact with objects to accomplish high-level tasks such as preparing meals and searching for objects. To achieve such tasks, robots need semantic world models, defined as object-based representations of the world involving task-level attributes. In this work, we address the problem of estimating(More)
Planning in large state-action spaces requires hierarchical abstraction for efficient computation. We introduce a new hierarchical planning framework called Abstract Markov Decision Processes (AMDPs) to find efficient solutions that, although possibly suboptimal, can solve complex planning problems in a fraction of the time needed for ordinary MDPs. AMDPs(More)