EXTENDED ABSTRACT: This paper introduces a new modeling paradigm for developing decision process representation called Decision Process Petri Nets (DPPN). It extends the place-transitions Petri net theoretic approach by including the Markov decision process. Placetransitions Petri nets (PN) are used for process representation taking advantage of the formal semantic and the graphical display. Ma...

Collision-tolerant trajectory planning is the consideration that collisions, if they are planned appropriately, enable more effective path planning for robots capable of handling them. A mixed integer programming (MIP) optimization formulation demonstrates the computational practicality of optimizing trajectories that comprise planned collisions. A damage quantification function is proposed, an...

In this paper we introduce a new modeling paradigm for developing a decision process representation called the Colored Decision Process Petri Net (CDPPN). It extends the Colored Petri Net (CPN) theoretic approach including Markov decision processes. CPNs are used for process representation taking advantage of the formal semantic and the graphical display. A Markov decision process is utilized a...

This paper exploits the computing power of widely available multi-core machines to accelerate the trajectory planning by parallelisation of the search algorithm. In particular we investigate the approach that schedules the workload on the cores using the hashing function based on the geographical partitioning of the search space. We use this approach to parallelize the AA* algorithm. In our sol...

In the paper we present a solution to the optimal trajectory planning problem subject to constraints given by the actuator torques and velocities, and the task. The main result is a trajectory planning algorithm which enables the calculation of the optimal motion due to the given requirements and taking into account the dynamics of the manipulator. The dynamic model of the manipulator in the pa...

A new trainable trajectory formation system for facial animation is here proposed that dissociates parametric spaces and methods for movement planning and execution. Movement planning is achieved by HMM-based trajectory formation. Movement execution is performed by concatenation of multi-represented diphones. Movement planning ensures that the essential visual characteristics of visemes are rea...

This paper develops a motion planning algorithm which exploits symmetry in distributed systems to reduce complexity and motion planning design time. The motion planning computations are carried out on a reduced order system, then extended to larger-order equivalent systems in such a way that the objectives of the larger system are satisfied and collision avoidance is guaranteed. The algorithm m...

As part of an ongoing collaborative effort with the Ford Motor Company, our research aims to develop practical and efficient trajectory planning tools for automotive painting. This paper documents our efforts to develop analytic deposition models for electrostatic rotating bell (ESRB) atomizers, which have recently become widely used in the automotive painting industry. Conventional deposition ...

This paper proposes a sampling based kinodynamic planning technique for planning informative trajectories for a sensing robot in a spatiotemporal environmental field. The robot uses a Kalman-Bucy filter to estimate the spatiotemporal field. The proposed algorithm finds a trajectory for the robot that minimizes a metric on the error covariance matrix of the field estimate. Since the error covari...

As part of an ongoing collaborative effort with the Ford Motor Company, our research aims to develop practical and efficient trajectory planning tools for automotive painting. This paper documents our efforts to develop analytic deposition models for electrostatic rotating bell (ESRB) atomizers, which have recently become widely used in the automotive painting industry. Conventional deposition ...