2009 Rolls Royce Phantom

MSRP Range: $380,000 - $450,000 | More Details
Value Rating:
Fuel Economy: 13 MPG city / 19 MPG highway
Bodystyles: Sedan, Convertible
Engines: 6.7L V12

exus

MSRP Range: $34,470 | More Details
Value Rating: Excellent
Fuel Economy: 19 MPG city / 27 MPG highway
Bodystyles: Sedan
Engines: 3.5L V6

What will "luxury car" mean in 2030

It's virtually tradition in the automotive industry that the features that will be found on the economy cars of tomorrow first appear on the luxury cars of today. To get a peek at what lies in store for the average driver, one merely needs to do a little window shopping at a high-end car dealership.


2009 Volvo C70
Manan Vatsyayana/AFP/Getty Images
Today's luxury cars, like the 2009 Volvo C70, shown in New Delhi, India, in January 2008, boast features that will be found on most cars in the future.



Although this custom may offend one's egalitarian sensibility, it makes sense from an economic perspective. Emergent technology is usually created on a limited scale, not in mass production. So it follows that because this technology is rare, it should be more expensive. Once it's found on widely produced automobiles, the cost for high-end technology will decrease.


­But for a luxury car to be a luxury car, its features have to stay ahead of the innovative curve. So to get an idea of what lays in store for luxury cars, we have to gaze into the crystal ball that is the concept car. A concept car is one that's not yet in production -- and may never make it there. Instead, concept cars often represent the cutting edge of technology and design. In many cases, the technology found aboard concept cars will be stripped for parts. Some aspects will be discarded; some will be used in mass-produced automobiles. If the concept cars emerging from designers' minds these days are any indication of what "luxury" will mean in 2030, then future car buyers have a lot to look forward to.

Control

The mechanical structure of a robot must be controlled to perform tasks. The control of a robot involves three distinct phases - perception, processing, and action (robotic paradigms). Sensors give information about the environment or the robot itself (e.g. the position of its joints or its end effector). This information is then processed to calculate the appropriate signals to the actuators (motors) which move the mechanical.

The processing phase can range in complexity. At a reactive level, it may translate raw sensor information directly into actuator commands. Sensor fusion may first be used to estimate parameters of interest (e.g. the position of the robot's gripper) from noisy sensor data. An immediate task (such as moving the gripper in a certain direction) is inferred from these estimates. Techniques from control theory convert the task into commands that drive the actuators.

At longer time scales or with more sophisticated tasks, the robot may need to build and reason with a "cognitive" model. Cognitive models try to represent the robot, the world, and how they interact. Pattern recognition and computer vision can be used to track objects. Mapping techniques can be used to build maps of the world. Finally, motion planning and other artificial intelligence techniques may be used to figure out how to act. For example, a planner may figure out how to achieve a task without hitting obstacles, falling over, etc.

Control systems may also have varying levels of autonomy. Direct interaction is used for haptic or tele-operated devices, and the human has nearly complete control over the robot's motion. Operator-assist modes have the operator commanding medium-to-high-level tasks, with the robot automatically figuring out how to achieve them. An autonomous robot may go for extended periods of time without human interaction. Higher levels of autonomy do not necessarily require more complex cognitive capabilities. For example, robots in assembly plants are completely autonomous, but operate in a fixed pattern.

Human interaction

If robots are to work effectively in homes and other non-industrial environments, the way they are instructed to perform their jobs, and especially how they will be told to stop will be of critical importance. The people who interact with them may have little or no training in robotics, and so any interface will need to be extremely intuitive. Science fiction authors also typically assume that robots will eventually be capable of communicating with humans through speech, gestures, and facial expressions, rather than a command-line interface. Although speech would be the most natural way for the human to communicate, it is quite unnatural for the robot. It will be quite a while before robots interact as naturally as the fictional C-3PO.

Environmental interaction and navigation

Robots also require navigation hardware and software in order to anticipate on their environment. In particular unforeseen events (eg people and other obstacles that are not stationary) can cause problems or collisions. Some highly advanced robots as ASIMO, EveR-1, Meinü robot have particular good robot navigation hardware and software. Also, self-controlled car, Ernst Dickmanns' driverless car and the entries in the DARPA Grand Challenge are capable of sensing the environment well and make navigation decisions based on this information. Most of the robots include regular a GPS navigation device with waypoints, along with radar, sometimes combined with other sensor data such as LIDAR, video cameras, and inertial guidance systems for better navigation in between waypoints.

Rolling robots

For simplicity, most mobile robots have four wheels. However, some researchers have tried to create more complex wheeled robots, with only one or two wheels.

* Two-wheeled balancing: While the Segway is not commonly thought of as a robot, it can be thought of as a component of a robot. Several real robots do use a similar dynamic balancing algorithm, and NASA's Robonaut has been mounted on a Segway.[27]
* Ballbot: Carnegie Mellon University researchers have developed a new type of mobile robot that balances on a ball instead of legs or wheels. "Ballbot" is a self-contained, battery-operated, omnidirectional robot that balances dynamically on a single urethane-coated metal sphere. It weighs 95 pounds and is the approximate height and width of a person. Because of its long, thin shape and ability to maneuver in tight spaces, it has the potential to function better than current robots can in environments with people.[28]
* Track Robot: Another type of rolling robot is one that has tracks, like NASA's Urban Robot, Urbie.[29]

[edit] Walking robots
iCub robot, designed by the RobotCub Consortium

Walking is a difficult and dynamic problem to solve. Several robots have been made which can walk reliably on two legs, however none have yet been made which are as robust as a human. Many robots have also been build that walk on more than 2 legs; these robots being significantly more easy to construct. Hybrids too have been proposed in movies as iRobot, where they walk on 2 legs and switch to 4 (arms+legs) when going to a sprint. Typically, robots on 2 legs can walk well on flat floors, and can occasionally walk up stairs. None can walk over rocky, uneven terrain. Some of the methods which have been tried are:

* ZMP Technique: The Zero Moment Point (ZMP) is the algorithm used by robots such as Honda's ASIMO. The robot's onboard computer tries to keep the total inertial forces (the combination of earth's gravity and the acceleration and deceleration of walking), exactly opposed by the floor reaction force (the force of the floor pushing back on the robot's foot). In this way, the two forces cancel out, leaving no moment (force causing the robot to rotate and fall over).[30] However, this is not exactly how a human walks, and the difference is quite apparent to human observers, some of whom have pointed out that ASIMO walks as if it needs the lavatory.[31][32][33] ASIMO's walking algorithm is not static, and some dynamic balancing is used (See below). However, it still requires a smooth surface to walk on.
* Hopping: Several robots, built in the 1980s by Marc Raibert at the MIT Leg Laboratory, successfully demonstrated very dynamic walking. Initially, a robot with only one leg, and a very small foot, could stay upright simply by hopping. The movement is the same as that of a person on a pogo stick. As the robot falls to one side, it would jump slightly in that direction, in order to catch itself.[34] Soon, the algorithm was generalised to two and four legs. A bipedal robot was demonstrated running and even performing somersaults.[35] A quadruped was also demonstrated which could trot, run, pace, and bound.[36] For a full list of these robots, see the MIT Leg Lab Robots page.
* Dynamic Balancing or controlled falling:A more advanced way for a robot to walk is by using a dynamic balancing algorithm, which is potentially more robust than the Zero Moment Point technique, as it constantly monitors the robot's motion, and places the feet in order to maintain stability.[37] This technique was recently demonstrated by Anybots' Dexter Robot,[38] which is so stable, it can even jump.[39] Another example is the TU Delft Flame.
* Passive Dynamics: Perhaps the most promising approach utilizes passive dynamics where the momentum of swinging limbs is used for greater efficiency. It has been shown that totally unpowered humanoid mechanisms can walk down a gentle slope, using only gravity to propel themselves. Using this technique, a robot need only supply a small amount of motor power to walk along a flat surface or a little more to walk up a hill. This technique promises to make walking robots at least ten times more efficient than ZMP walkers, like ASIMO.