Quantitative temporal constraints are an essential requirement for many planning domains. The HTN planning paradigm has proven to be better suited than other approaches to many applications. To date, however, efficiently integrating temporal reasoning with HTN planning has been little explored. This paper describes a means to exploit the structure of a HTN plan in performing temporal propagatio...

Episodic memory modeling enjoys increasing interest in virtual agents, autonomous companions or computer games research communities. To evaluate memory models, it is often necessary to “fill” them with appropriate data streams of activities corresponding to what would happen to a real human during a particular time period. However, such activity corpora, freely available, are, to our best knowl...

For an agent to act successfully in a complex and dynamic environment (such as a computer game) it must have a method of generating future behaviour that meets the demands of its environment. One such method is anytime planning. This paper discusses the problems and benefits associated with making a planning system work under the anytime paradigm, and introduces AnytimeUMCP (A-UMCP), an anytime...

planning robot trajectory is a complex task that plays a significant role in design and application of robots in task space. the problem is formulated as a trajectory optimization problem which is fundamentally a constrained nonlinear optimization problem. open-loop optimal control method is proposed as an approach for trajectory optimization of cable parallel manipulator for a given two-end-po...

Complex manipulation tasks require careful integration of symbolic reasoning and motion planning. This problem, commonly referred to as Task Motion Planning (TAMP), is even more challenging if the workspace non-static, e.g. due human interventions perceived with noisy non-ideal sensors. work proposes an online approximated TAMP method that combines a geometric module planner standard task in re...