SENSITIVE SKIN DESIGNING AN ALL-SENSITIVE ROBOT ARM MANIPULATOR in .NET framework

Creator PDF417 in .NET framework SENSITIVE SKIN DESIGNING AN ALL-SENSITIVE ROBOT ARM MANIPULATOR
SENSITIVE SKIN DESIGNING AN ALL-SENSITIVE ROBOT ARM MANIPULATOR
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alternative move so slowly that those forces would be contained is simply not realistic. Then, why not use vision instead The short answer is that since an arm manipulator operates in a workspace that is comparable in size to the arm itself, vision will be less effective for motion planning than proximity sensing that covers the whole arm. By and large, humans and animals use whole-body (tactile) sensing rather than vision for motion planning at small distances to sit down comfortably in a chair, to delicately avoid an overactive next-chair neighbor on an aircraft ight, and so on. See more on this below. This discussion suggests that except for some speci c tasks that require a physical contact of the robot with other objects such as the robot assembly, where the contact occurs in the robot wrist tactile sensing is not a good sensing media for robot motion planning. Proximity sensing is a better sensing candidate for the robot sensitive skin.
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Ability to Measure Distances. When the robot s proximal sensor detects an obstacle that has to be dealt with to avoid collision, it is useful to know not only which point(s) of the robot body is in danger, but also how far from that spot the obstacle is. In Figure 8.4, if in addition to learning from sensor P about a nearby obstacle the arm would also know the obstacle s distance from it for example, that the obstacle is in position O and not O its collision-avoiding maneuver could be much more precise. Similar to a higher sensor resolution, an ability to measure distances to obstacles can improve the dexterity of robot motion. In mobile robots this property is common, with stereo vision and laser ranger sensors being popular choices. For robot arms, given the full coverage requirement, realizing this ability is much harder. For example, at the robot-to-obstacle distances that we are interested in, 5 to 20 cm, the time-of- ight techniques used in mobile robot sensors are hardly practical for infrared sensors: The light s time of ight is too short to detect
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Figure 8.4 Knowing the distance between the robot and a potential obstacle translates into better dexterity of the arm s motion.
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SALIENT CHARACTERISTICS OF A SENSITIVE SKIN
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it. Ultrasound sensors can do this measurement easily, but their resolution is not good. One possible strategy is to adhere to a binary yes no measurement. In a sensor with limited sensitivity range, say 20 cm, the yes signal will tell the robot that at the time of detection the object was at a distance of 20 cm from the robot body. The technique can be improved by replacing a single sensor by a small cluster of sensors, with each sensor in the cluster adjusted to a different turn-on sensitivity range. The cluster will then provide a crude measurement of distance to the object.
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Sensors Physical Principle of Action. Vision sensing being as powerful as we know it, it is tempting to think of vision as the best candidate for the robot whole-body sensing. The following discussion shows that this is not so: Vision is very useful, but not universally so. Here are two practical rules of thumb:
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1. When the size of the workspace in which the robot operates is signi cantly larger than the robot s own dimensions as, for example, in the case of mobile robot vehicles vision (or a laser ranger sensor) is very useful for motion planning. 2. When the size of the robot workspace is comparable to the robot dimensions as in the case of robot arm manipulators proximal sensing other than vision will play the primary role. Vision may be useful as well for example, for the task execution by the arm end effector. Let us start with mobile robot vehicles. When planning its path, a mobile robot s motion control unit will bene t from seeing relatively far in the direction of intended motion. If the robot is, say, about a meter in diameter and standing about a meter tall, with sensors on its top, seeing the scene at 10 20 meters would be both practical and useful for motion planning. Vision is perfect for that: Similar to the use of human vision, a single camera or, better, a two-camera stereo pair will provide enough information for motion planning. On the other hand, remember, the full coverage requirement prescribes an ability to foresee potential collisions at every point of the robot body, at all times. If the mobile robot moves in a scene with many small obstacles, possibly occluding each other and possibly not visible from afar, so that they can appear underneath and at the sides, even a few additional cameras would not suf ce to notice those details. The need for sensing in the vicinity of the robot becomes even stronger for arm manipulators. The reason is simple: Since the arm s base is xed, it can reach only a limited volume de ned by its own dimensions. Thinking of vision as a candidate, where would we attach vision cameras to guarantee the full coverage Should they be attached to the robot, or put on the walls of the robot work cell, or both A simple drawing would show that in any of these options even a large number of cameras which is impractical anyway would not guarantee the full sensing coverage. Occlusion of one robot link by another link, or by cables that carry
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