This paper describes the exploration component of MOBOT-IV, an autonomous mobile robot for indoor-applications. MOBOT-IV has no preloaded world-model, but builds up an internal map while exploring the environment using its optical range finder. A method is presented for the autonomous and systematic construction of a 2D-map of the vehicles environment. Besides a line based geometric representation of the obstacles a topological abstraction of the robots environment is generated representing the room structure.>

One of the problems of autonomous mobile systems is the continuous tracking of position and orientation. In most cases, this problem is solved by dead reckoning, based on measurement of wheel rotations or step counts and step width. Unfortunately dead reckoning leads to accumulation of drift errors and is very sensitive to slipping. In this paper an algorithm for tracking position and orientation is presented, it is nearly independent from odometry and its problems with slipping. To achieve these results, a rotating range-finder is used, delivering scans of the environmental structure. The properties of this structure are used to match the scans from different locations in order to find their translational and rotational displacement. For this purpose derivatives of range-finder scans are calculated which can be used to find position and orientation by crosscorrelation.>

The environment mapping and navigation components of MOBOT-III are described. MOBOT-III is a laser-radar-based autonomous mobile robot designed to operate in an unknown indoor environment with moving obstacles. A simple environment representation that is continuously updated while MOBOT-III moves through the environment is used as the basis for the navigation method described. The environment representation is maintained by sensor data processing components, and a world model is built up successively as the system explores its environment.>

A description is given of a data-processing structure for real-time systems with sensory feedback and a distributed computer architecture that supports it. The computer system is implemented within an autonomous mobile robot and is based on a set of independent processing modules, each of which consists of a processing core, a transport unit, and a common memory between them. Communication between modules is done in two ways. For command transportation, a direct point-to-point connection is used and transport of raw and processed sensor data is done by broadcasting. Transportation is controlled by an adjustable timetable, which is maintained by the supervisor, who slows down the driving speed and adjusts the timetable if the module does not process the given task in time. This facility allows speed of the robot to be adapted to the current processing capacity and to the complexity of the environment.>

The design of a simple hardware memory allocator is described, which allocates blocks of different lengths L = 2h = K, K-1,..., K-n in a memory according to the buddy system algorithm. The binary tree, representing the distribution of free and used blocks in memory is mapped into a set of shift registers. They are connected for end-around shifting and clocked with frequencies different for each register, preserving thereby the internal structure of the binary tree. A small counter, attached to each shift register in the set holds the address of the first free block and can be read out on request within 0.5 μs. A simple control unit realizes the algorithm. Having answered a request the system needs about 130 μs to compute the addresses of free blocks in a total of 511 blocks managed by the device.