The Partially-Observable Markov Decision Process (POMDP) is a general framework to determine reward-maximizing action policies under noisy action and sensing. However, determining an optimal policy for POMDPs is often intractable for robotic tasks due to the PSPACE-complete nature of the computation required. Several recent solvers have been introduced that expand the size of problems that can ...

This paper deals with motion planning for a mobile robot moving on a hilly three dimensional terrain and subjected to strong physical interaction constraints. The main contribution of this paper is a planning method which takes into account the dynamics of the robot, the robot/terrain interactions, the kinematic constraints of the robot, and classical constraints. The basic idea of our method i...

Oceanographic images obtained from environmental satellites by a wide range of sensors allow characterizing natural phenomena through different physical measurements. For instance Sea Surface Temperature (SST) images, altimetry data and ocean color data can be used for characterizing currents and vortex structures in the ocean. The purpose of this thesis is to derive a relatively complete frame...

Motion in image sequences can result from the motion of the observer (egomotion) and from the presence of independently moving objects (IMOs) within the eld of view of the observer. Any vision system intended for an observer capable of motion needs the ability to distinguish between these two possibilities in order to successfully perform navigation and collision avoidance tasks. One approach t...

Constraints play a central role in the analysis and planning of robot motion. We suggest that constraints form an appropriate language with which to program robot motion as well and describe the Least Constraint framework.

Runid: Bashful: probabilistic camera motion with conservative threshold 1 for high precision Runid: Doc: probabilistic camera motion with conservative threshold 2 for high precision Runid: Dopey: probabilistic camera motion with relaxed constraints (threshold 1) for high recall Runid: Grumpy: probabilistic camera motion with relaxed constraints (threshold 2) for high recall Runid: Happy: optica...

This chapter describes kinodynamic motion planning and its application. Kinodynamics is the discipline that tries to solve kinematic constraints and dynamical constraints simultaneously. By using kinodynamic motion planning, control inputs can be generated in a much simpler way, compared to the conventional motion planning that solves kinematics and dynamics separately. After briefly overviewin...

This dissertation presents a framework for estimation of motion fields in 2D images, 3D volumes and multi-dimensional signal registration. The primary application is motion compensation for sequences of medical images and volumes with contrast agents. The framework implies motion estimation in two steps where the intermediate result is constraints on the local motion vectors. One algorithm gene...

In this paper, we present a hybrid approach to motion data manipulation. Motion signal is decomposed into multi-resolution levels with wavelet analysis. The coarse level represents the globe pattern of a motion signal while the fine levels describe the individual styles. Special motion style can be highlighted through enhancing the corresponding level content and can be fused into other motions...

Multiview analysis of scenes includes the study of sceneindependent constraints satisfied by a configuration of cameras for all types of scenes as well as the study of viewindependent constraints satisfied by any camera on a configuration of points. In this paper, we derive new constraints involving configurations of points that move with constant velocity, with constant acceleration, and for u...