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Assume the bug s target location is somewhere on the other side of the obstacle One way for it to continue its motion is to rst pass around the obstacle The bug has only two options: It can pass the obstacle from the left or it can pass it from the right, clockwise or counterclockwise If neither option leads to success let us assume it is a smart bug, with a reasonably good motion planning skills the goal is not achievable In this case, by slightly exaggerating the bug s stubbornness, we will note that eventually the bug will come back to the point on the obstacle where it started It took only one simple going around, all in one direction, to explore the whole obstacle That is the essence of the 2D case Imagine now a y that is ying around a room that is, in 3D space.

spoke: Jimmy Marianne They looked up So entirely stunned from the game, they didn t ask how Harvey knew their names But it freaked me out that he knew them by name They both looked up at Harvey The husband was still fishing in his pockets and the wife had her hand in her purse You re going to be late for the show Let me walk you outside, he said And with that, they quickly gathered up their belongings He put his arms around them, escorted them outside onto Amsterdam Avenue, where through the window I could see him chatting with them They started to laugh He handed the $100 to the husband, who initially refused, and then Harvey leaned in and whispered something in his ear Whatever he said did the trick and soon the couple was happily trotting down the street on their way to the show.

Imagine that on its way the y encounters a (3D) obstacle say, a child s balloon hanging on a string Now there is an in nite number of routes the y can take to pass around the obstacle The y would need to make a great many loops around the obstacle in order to explore it completely That s the fundamental dif culty of the 3D case; in theory it takes an in nitely long path to explore the whole obstacle, even if its dimensions and volume are nite and modest1 The point is that while in the 2D case a mobile robot has a theoretically guaranteed nite solution, no such solution can be guaranteed for a 3D mobile robot The 3D sensor-based motion planning problem is in general intractable The situation is more complex, but also not as hopeless, for 3D arm manipulators Try this little experiment.

Architectural resource sharing was discussed in an earlier chapter, whereby portions of the design that can be used for different blocks of functionality are reused via steering logic. At a high level, this type of architecture can dramatically reduce the overall area with a penalty that may include throughput if the operations are not mutually exclusive. Resource sharing on the synthesis optimization level typically operates on groups of logic between register stages. These simpler architectures can be boiled down to simple logical and often arithmetic operations. A synthesis engine that supports resource sharing will identify similar arithmetic operations that are mutually exclusive and combine the operations via steering logic. For instance, consider the following example.

Fix your shoulder and try to move your hand around a long vertical pole Unlike a y that can make as many circles around the pole as it wishes, your hand will make about one circle around the pole and stop What holds it from continuing moving in the same direction is the arm s kinematics and also the fact that the arm s base is nailed down The length of your arm links is nite, the links themselves are rigid, and the joints that connect the links allow only so much motion These are natural constraints on your arm movement The same is so for robot arm manipulators In other words, the kinematic constraints of an arm manipulator impose strong limitations on its motion This fact makes the problem of sensor-based motion planning for 3D arm manipulators manageable.

When Harvey sat back down, the rest of the crowd had dissipated and we were alone in the booth He said: Did you see, Harry, he started, did you see what just happened there I had to admit that the only thing that I had seen were two stupid people overpaying for currency I told him so Okay Does that apply to trading I thought for a moment This depressed me I didn t want to think about my losses from that morning I am sure that it does, I replied I am sure that there is a lesson in here for me I honestly don t want to talk about it, though I paused The truth struck me then: Harvey would soon leave and I would never trade successfully Soon I would return to work at some crap law firm if anyone would still take me.

The hope is that the arm kinematics can be effectively exploited to make the problem tractable Furthermore, those same constraints promise a constructive test of target reachability, similar to those we designed above for mobile robots and 2D arm manipulators As noted by Brooks [102], the motion planning problem for a manipulator with revolute joints is inherently dif cult because (a) the problem is nondecomposable, (b) there may be dif culties associated with rotations, (c) the space representation and hence the time execution of the algorithm are exponential in the number of robot s degrees of freedom of the objects involved, and (d) humans are especially poor at the task when much reorientation is needed, which makes it dif cult to.