Algorithms for planning under uncertainty require accurate action models that explicitly capture the uncertainty of the environment. Unfortunately, obtaining these models is usually complex. In environments with uncertainty, actions may produce countless outcomes and hence, specifying them and their probability is a hard task. As a consequence, when implementing agents with planning capabilitie...

In May 1999, as part of a unique technology validation experiment onboard the Deep Space One spacecraft, the Remote Agent became the first complete autonomous spacecraft control architecture to run as flight software onboard an active spacecraft. As one of the three components of the architecture, the Remote Agent Planner had the task of laying out the course of action to be taken, which includ...

In the RETSINA multi-agent system, each agent is provided with an internal planning component—the RETSINA planner. Each agent, using its internal planner, formulates detailed plans and executes them to achieve local and global goals. Knowledge of the domain is distributed among the agents, therefore each agent has only partial knowledge of the state of the world. Furthermore, the domain changes...

We describe APPSSAT, an anytime probabilistic contingent planner based on ZANDER, a probabilistic contingent planner that operates by converting the planning problem to a stochastic satisfiability (Ssat) problem and solving that problem instead [1]. The values of some of the variables in an Ssat instance are probabilistically determined; APPSSAT considers the most likely instantiations of these...

I present a language for specifying planning problems in which there are external events, that is, events beyond the direct control of the planner which may happen while a plan is being executed. The language is based on Miller and Shanahan’s representation of narratives in the situation calculus. I describe an implemented planner that produces correct plans for this language, and discuss how s...

In this letter, we propose a lightweight yet effective Topology Guided Kinodynamic planner (TGK-Planner) for quadrotor aggressive flights with limited onboard computing resources. The proposed system follows the traditional hierarchical planning workflow, novel designs to improve robustness and efficiency in both pathfinding trajectory optimization sub-modules. Firstly, topology guided graph, w...

Planning problems are, in general, PSPACE-complete; large problems, especially multi-agent with required co-ordination, can be intractable or impractical to solve. Factored planning and both address this by separating into tractable sub-problems, but there are limitations the expressivity of existing planners ability handle tightly coupled problems. This paper presents EGOPLAN, a framework whic...

Planning a new logistics center is a quite difficult job. Depending on the requirements there are a great number of possible design versions. The planner has to consider not only the present but also the future requirements. Up to now, the planner decides on the basis of experience which system will perform the requested services best. This paper illustrates the redesign of a new order-picking ...