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Figure 8.10 Robot teleoperation. The operator controls the main (slave) robot arm by moving a small master arm seen on the right. The robot is expected to roughly follow the path indicated in real time by the operator, while using its own sensing and intelligence to avoid a chess player in its work space. The result is a path that is as close as possible to the path shown by the operator, short of collisions.

The penalty to pay for unrolling loops such as this is an increase in area. The iterative implementation required a single register and multiplier (along with some control logic not shown in the diagram), whereas the pipelined implementation required a separate register for both X and XPower and a separate multiplier for every pipeline stage. Optimizations for area are discussed in the 2.

Figure 8.11 Robot teleoperation. Here the operator has attempted to hurt a student sitting in the robot work space. After bringing the (slave) robot right above the student s head (second picture), the operator moves the master arm sharply down, expecting the robot to repeat this motion. The robot starts in this direction, but then hesitates and stops. Note the difference between the robot and master arms positions (second picture); the latter shows a clear intention to bring the robot much lower than it went. Eventually the operator moves the master arm toward us, and the robot follows (third picture). Note: The videos that supplied pictures for Figures 8.9 to 8.11 can be seen in full on the web, http://aaaprod.gsfc.nasa.gov/Project/public html-NASA/LaRue-Lumelsty.htm.

A low-latency design is one that passes the data from the input to the output as quickly as possible by minimizing the intermediate processing delays. Oftentimes, a low-latency design will require parallelisms, removal of pipelining, and logical short cuts that may reduce the throughput or the max clock speed in a design.

I didn t know what to say was John in danger of losing his job That was news to me, certainly, and I wasn t going to spend any time delving into that problem Maybe that s why John was so excited about getting a meeting with Anderson to do the work on the forex fund Well, keeping him at the firm seems like a good idea to me, I said Really Is that what John told you No I just thought it sounded like the right thing to say So John didn t tell you, he said Tell me what Now I was more interested He wants to leave the firm and come down and work with me This made sense.

Figure 8.12 A robot dancing with a ballerina (frames from a video). At all times the robot moves so as to be close to the ballerina while avoiding collisions with her. Note that at times the ballerina moves while not looking at the robot. She expects the robot to behave the same way as she would expect from a human partner stepping in and out as necessary and reacting in a gentle human way. This expectation relates to the whole bodies of both partners. There is no preprogrammed motion on the robot part.

way the robot encountered obstacles two students oblivious to the robot and bending slightly over the chess board; it went around and above the students heads and continued on its trajectory. The experiment in Figure 8.10 relates to the teleoperation setting 2 above. The robot is controlled by an operator using a small master arm that can be seen on the right, and also by its own motion planning algorithms. Unlike a common teleoperation, here we have a human machine team, where each partner does what he/she/it is best at. The operation is thus is a real-time synergy of human and robot intelligence. The operator would move the master arm in a rather cavalier fashion, without regard for a human inside the robot workspace and without attempting a precise trajectory. The goal here was for the main (slave) robot to reach the right side of the scene and into the large loop. The operator quickly moves the master arm ahead of the robot, paying no attention to the human obstacle in the scene. When encountering the previously unknown obstacle a person playing chess the robot goes around the player s head; lowers slightly, trying to get to the operator s path; and then continues on the operator-dictated path. The pictures in Figure 8.11 also relate to the teleoperation setting 2. Along the way the operator attempts to make the robot hit the human present in the robot workspace. This scene surely looks more dramatic in a videotape: The viewer sees that the operator, after rst bringing the robot right above the human head, decisively pushes the master arm straight down; the viewer also sees how, after starting in this direction, the robot freezes in the air, refusing to hurt the

Referring back to our power-of-3 example, there is no obvious latency optimization to be made to the iterative implementation as each successive multiply operation must be registered for the next operation. The pipelined implementation, however, has a clear path to reducing latency. Note that at each pipeline stage, the product of each multiply must wait until the next clock edge before it is propagated to the next stage. By removing the pipeline registers, we can minimize the input to output timing: