We explain how most conventional approaches to the problem of visually guided robot navigation are fundamentally restricted. Starting with a specification of the requirements of a general purpose visually guided robot which includes, robustness, autonomy, flexibility and scalability, we then develop an approach to the solution of map building and path planning which operates within a learning f...

Automatic vehicle location (AVL) data can be used for a variety of operational and planning purposes at a transit agency. One possible application is for passenger itinerary planning, where the passenger seeks to go from an origin to a destination in some “optimal” way. The AVL data give actual vehicle arrival and departure times, which in turn can give more robust itineraries to passengers. Th...

In context-aware route planning, there is a set of transportation agents each with a start and destination location on a shared infrastructure. Each agent wants to find a shortest-time route plan without colliding with any of the other agents, or ending up in a deadlock situation. We present a single-agent route planning algorithm that is both optimal and conflict-free. We also present a set of...

In this paper, we consider planning in stochastic shortest path (SSP) problems, a subclass of Markov Decision Problems (MDP). We focus on medium-size problems whose state space can be fully enumerated. This problem has numerous important applications, such as navigation and planning under uncertainty. We propose a new approach for constructing a multi-level hierarchy of progressively simpler ab...

The k-goal problem is a generalization of the Shortest Path Problem (SPP) in which the task is to solve k SPP problems, such that all the problems share the same start vertex. kGP was introduced to the heuristic search community for building an Incremental Roadmap Spanner technique (Dobson and Bekris 2014), which is a useful construct in motion plannin for robotics. But kGP has many other appli...

Most previous theoretical work on motion planning for a group of robots has addressed the problem of path planning for the individual robots sequentially, in geometrically simple regions of Euclidean space (e.g., a planar region containing polygonal obstacles). In this paper, we define a version of the motionplanning problem in which the robots move simultaneously. We establish conditions under...

This paper presents a path planning method for a mobile robot in an environment that is unknown and can change. This method relies on continually sensing the local environment. Robot and personnel safety is a dominant and essential requirement for this path planning method. A new method for obtaining safe directions in a tessellated map of the environment is introduced. Linear combination of ve...

The paper presents a new path planning and replanning algorithm based on two-dimensional occupancy grid map of the environment, which integrates the focused D* (FD*) algorithm and Witkowski’s algorithm. The FD* algorithm is used for fast replanning and Witkowski’s algorithm is used for generating all optimal paths in the grid map. Our algorithm finds the shortest path in the geometrical space b...

In this paper an algorithm is presented to find a shortest path between two points in the plane amidst growing discs. That is, as the “point” moves through the plane, the discs grow at an a priori known rate. We present an O(n logn) algorithm and a fast implementation. The problem is motivated from robotics, where motion planning in dynamic environments is a great challenge. Our algorithm can b...

Manipulating the Space Station Remote Manipulator (SSRMS), known as “Canadarm II”, on the International Space Station (ISS) is a very challenging task. The astronaut does not have a direct view of the scene of operation and must rely on cameras mounted on the manipulator and at strategic places of the environment where it operates. In this paper, we present Roman Tutor, an intelligent robotic s...