As discussed in class, two of the primary control paradigms for mobile robots have historically been the deliberative paradigm and the reactive paradigm. As the term “deliberative paradigm” implies, robot software architectures constructed using the deliberative paradigm should be good at careful reasoning about the world. However, they may not be well suited to tasks that do not involve or permit much deliberation. Similarly, the term “reactive paradigm” implies that robot software architectures constructed using the reactive paradigm should be good at fast responses to newly sensed information but may not be well suited to tasks that require forethought or planning.
Consider the following mission and environment description:
The robot is to act as a guide in Devon Energy Hall (DEH) and Rawl Engineering Practice Facility (REPF), providing either of two types of guide services to parties of one or more people: (1) point-to-point (P2P) and (2) tour. As a P2P guide, it guides a party from a starting location to an ending location by an effective route. (An effective route is one that tries to minimize distance, time, energy, chance of getting lost, and traffic encountered.) As a tour guide, it guides a party on a tour of the buildings, showing building highlights and telling its party about them. Building highlights include the Software Studio, the practice bays in REPF (as viewed from the second floor walkway), the atrium in DEH and first floor rooms visible from it (the computer lab, electronics lab, team room, and board room), the main CS/ECE office in DEH, the clean room and terrace on the fifth floor, and the greatest highlight of all, Prof. Hougen’s office (DEH 242). The order of the highlights on the tour will depend on the starting location of the tour, forming an effective route from the starting location and including all highlights. The robot may be engaged by a party approaching it and requesting guide services (of either kind) or by being remotely summoned to a location in either building where a party is waiting for it. If summoned, the robot will take an effective route to the waiting party.
The guide robot can access a floor plan of both buildings and the sidewalks and tunnel connecting them. The floor plan includes the locations of “permanent” elements such as walls, doors, stairs, and elevators. It also includes the “normal” locations of movable elements such as chairs, tables, lamps, desks, etc. (Note that while these items are movable by people in the buildings, they are too large and heavy for the robot to move significantly.) The floor plan also includes information on the floor surfaces of the buildings including “permanent” flooring such as tile, carpet, and cement and the normal locations of movable floor coverings such as rugs. All of these elements are individually included in the floor plan, so it is possible to distinguish between elements of different kinds on the floor plan.
The robot can traverse all of the horizontal surface types but may move more effectively or efficiently over one surface than another and cannot traverse stairs. There may also be people moving about in the environment. People will not actively attempt to impede the progress of the robot but neither will they actively attempt to assist the robot (e.g., by moving out of its way), unless asked. Effectively, the people can be considered to be moving obstacles which the robot must avoid unless it attempts to enlist their assistance. If assistance is requested by the robot, people may be assumed to help in small ways; for instance, they could move a bit to one side or another, open a nearby door, press a nearby button (in the elevator or on a powered/accessible door), or point to provide directions towards a destination (if known). However, a person will not go to great lengths to assist—a person will not guide the guide robot on its tour, for instance.
Since we have not yet extensively covered sensing, localization, planning, or many other robot capabilities that would be needed for this mission, you may assume that the robot is capable of sensing large objects in its environment (e.g., walls, chairs, people) although it may not be readily able to distinguish between them, that it can know its location within the specified environment to within several feet, and that it can plan routes within the specified environment.
Complete the following exercises:
Turn in via D2L an electronic copy of this assignment consisting of your typed responses to the exercises above. In total, your responses should run from 1.5 to 2.5 pages in length (roughly 80 characters per line, 50 lines per page). This does not count any diagrams or other figures that you may choose to include which may be of any size.