A mobile robot with a manipulator was developed for a security guard service application. The application image is that a robot patrols the building autonomously and checks for emergencies like fire, intruder, etc. On detecting an emergency the robot informs a remote operator who deals with the emergency by remotely operating the robot. The developed robot has the following functions to perform such a security service: autonomous navigation, master-slave manipulation system with force feedback, a remotely operated camera vision system with wide and stereoscopic view modes. The experiments conducted with the robot show that the robot can navigate autonomously in simple environments with a maximum speed of 1 m/s. A remote operator can perform door-opening using the master-slave manipulator and stereo viewing vision systems. This paper describes the various subsystems of the robot and some findings of the experiments.

A non-metric path planning algorithm, Curv1, is developed for moving a point automaton between two given points along a guide-track, amidst unknown obstacles. No physical mark is made on the guide-track and no position on distance information is used. The nonheuristic algorithm is shown to converge and an upper bound on the path length is derived. This nonmetric formulation is shown to be related to, and in some sense, a generalization of the maze-searching problem. For the curve-following task, the Curv1 algorithm is shown to be a generalization of the maze-searching Pledge algorithm (H. Abelson and E. DiSessa, 1980). The robustness of the algorithm makes it suitable for an industrial application of autonomous robot guide-track following.>

The problem of making a map of an unknown scene containing objects of arbitrary shapes is considered. A specific formulation of the terrain acquisition problem due to Lumelsky et al. is investigated. The motivation is to develop efflcient new algorithms and understand the basics of the problem. A new, generalized algorithm GenTer is developed. Varying a parameter (Y in GenTer produces a family of algorithms. A particular version of the generalized algorithm, called Terl, performs better on the average than the existing algorithm, the Sightseer Strategy. Terl offers a new feature called the Hierarchical Map Making, through which a good approximate map can be efflciently created.

The problem of generating a path between any two points for a point object in a 2D plane filled with unknown obstacles of arbitrary shapes is discussed. This problem is termed P1. The issue of worst-case path lengths is analysed in a general setting, independent of any particular algorithm. It is shown that there are two distinct approaches available to solve P1, dividing the set of all possible algorithms that solve P1 into two disjoint classes. The minimum worst-case path length possible in each class is determined and the universal lower bound on the worst case path length of any algorithm is found. The results are shown to be useful in developing algorithms and more general problem models.>

A nonheuristic path planning for moving a point object, or mobile automation (MA), in a two-dimensional plane, amidst unknown obstacles, is considered. A path is to be generated, point by point, using only the local information, like the MA's current position and whether it is in contact with an obstacle. A path-planning algorithm to solve this problem is proposed. The algorithm is used to realize the smallest worst-case path length possible in its category. The procedure for the algorithm is presented with explanations. Its various characteristics, such as local cycle creation, worst-case path length, target reachability conditions, etc. are dealt with. Its performance is compared with that of the existing algorithms. Examples showing the operation of the algorithm are presented. >