Distance estimation and collision prediction for on-line robotic motion planning

An efficient method for computing the minimum distance and predicting collisions between moving objects is presented. This problem has been incorporated in the framework of an in-line motion planning algorithm to satisfy collision avoidance between a robot and moving objects modeled as convex polyhedra. In the beginning the deterministic problem, where the information about the objects is assumed to be certain is examined. If instead of the Euclidean norm, L(sub 1) or L(sub infinity) norms are used to represent distance, the problem becomes a linear programming problem. The stochastic problem is formulated, where the uncertainty is induced by sensing and the unknown dynamics of the moving obstacles. Two problems are considered: (1) filtering of the minimum distance between the robot and the moving object, at the present time; and (2) prediction of the minimum distance in the future, in order to predict possible collisions with the moving obstacles and estimate the collision time

An optimal control strategy for collision avoidance of mobile robots in non-stationary environments

An optimal control formulation of the problem of collision avoidance of mobile robots in environments containing moving obstacles is presented. Collision avoidance is guaranteed if the minimum distance between the robot and the objects is nonzero. A nominal trajectory is assumed to be known from off-line planning. The main idea is to change the velocity along the nominal trajectory so that collisions are avoided. Furthermore, time consistency with the nominal plan is desirable. A numerical solution of the optimization problem is obtained. Simulation results verify the value of the proposed strategy

Robust Distributed Control Protocols for Large Vehicular Platoons with Prescribed Transient and Steady State Performance

In this paper, we study the longitudinal control problem for a platoon of vehicles with unknown nonlinear dynamics under both the predecessor-following and the bidirectional control architectures. The proposed control protocols are fully distributed in the sense that each vehicle utilizes feedback from its relative position with respect to its preceding and following vehicles as well as its own velocity, which can all be easily obtained by onboard sensors. Moreover, no previous knowledge of model nonlinearities/disturbances is incorporated in the control design, enhancing in that way the robustness of the overall closed loop system against model imperfections. Additionally, certain designer-specified performance functions determine the transient and steady-state response, thus preventing connectivity breaks due to sensor limitations as well as inter-vehicular collisions. Finally, extensive simulation studies and a real-time experiment conducted with mobile robots clarify the proposed control protocols and verify their effectiveness.Comment: IEEE Transactions on Control Systems Technology, accepte

A practical approach for minimum time control of the Spacecraft Control Laboratory Experiment (SCOLE), appendix A

The Space COntrol Laboratory Experiment (SCOLE) is a challenge for control engineering applications. This is a result of the system dynamics, the available measurement information, the actuator capabilities and finally the specified performance requirements set. Results on the use of Model Reference Adaptive Control were reported. In view of the necessity for rapid response, this work deals with an optimal control formulation, with a minimum time requirement and constrained input. A mathematical statement of the problem is presented. The time optimal control formulation is presented and the reasons that make such an approach not promising are discussed. As a result, a pseudo time-optimal control algorithm is discussed. The proposed approach is tested to see if it satisfies the design specifications, and finally a discussion and suggestions for further research are provided

Static chamber methane flux measurements in volcanic/geothermal areas: preliminary data from Sousaki and Nisyros (Greece)

Methane plays an important role in the Earth’s atmospheric chemistry and radiative balance being the second most important greenhouse gas after carbon dioxide. Methane is released to the atmosphere by a wide number of sources, both natural and anthropogenic, with the latter being twice as large as the former (IPCC, 2007). It has recently been established that significant amounts of geological methane, produced within the Earth’s crust, are currently released naturally into the atmosphere (Etiope, 2004). Active or recent volcanic/geothermal areas represent one of these sources of geological methane. But due to the fact that methane flux measurements are laboratory intensive, very few data have been collected until now and the contribution of this source has been generally indirectly estimated (Etiope et al., 2007). The Greek territory is geodynamically very active and has many volcanic and geothermal areas. Here we report on methane flux measurements made at two volcanic/geothermal systems along the South Aegean volcanic arc: Sousaki and Nisyros. The former is an extinct volcanic area of Plio-Pleistocene age hosting nowadays a low enthalpy geothermal field. The latter is a currently quiescent active volcanic system with strong fumarolic activity due to the presence of a high enthalpy geothermal system. Both systems have gas manifestations that emit significant amounts of hydrothermal methane and display important diffuse carbon dioxide emissions from the soils. New data on methane isotopic composition and higher hydrocarbon contents point to an abiogenic origin of the hydrothermal methane in the studied systems. Measured methane flux values range from –48 to 29,000 (38 sites) and from –20 to 1100 mg/mˆ2/d (35 sites) at Sousaki and Nisyros respectively. At Sousaki measurement sites covered almost all the degassing area and the diffuse methane output can be estimated in about 20 t/a from a surface of about 10,000 mˆ2. At Nisyros measurements covered the Stephanos and Kaminakia areas, which represent only a part of the entire degassing area. The two areas show very different methane degassing pattern with latter showing much higher flux values. Methane output can be estimated in about 0.25 t/a from an area of about 30,000 mˆ2 at Stephanos and about 1 t/a from an area of about 20,000 mˆ2 at Kaminakia. The total output from the entire geothermal system of Nisyros probably should not exceed 2 t/a

Emergence of good conduct, scaling and Zipf laws in human behavioral sequences in an online world

We study behavioral action sequences of players in a massive multiplayer online game. In their virtual life players use eight basic actions which allow them to interact with each other. These actions are communication, trade, establishing or breaking friendships and enmities, attack, and punishment. We measure the probabilities for these actions conditional on previous taken and received actions and find a dramatic increase of negative behavior immediately after receiving negative actions. Similarly, positive behavior is intensified by receiving positive actions. We observe a tendency towards anti-persistence in communication sequences. Classifying actions as positive (good) and negative (bad) allows us to define binary 'world lines' of lives of individuals. Positive and negative actions are persistent and occur in clusters, indicated by large scaling exponents alpha~0.87 of the mean square displacement of the world lines. For all eight action types we find strong signs for high levels of repetitiveness, especially for negative actions. We partition behavioral sequences into segments of length n (behavioral `words' and 'motifs') and study their statistical properties. We find two approximate power laws in the word ranking distribution, one with an exponent of kappa-1 for the ranks up to 100, and another with a lower exponent for higher ranks. The Shannon n-tuple redundancy yields large values and increases in terms of word length, further underscoring the non-trivial statistical properties of behavioral sequences. On the collective, societal level the timeseries of particular actions per day can be understood by a simple mean-reverting log-normal model.Comment: 6 pages, 5 figure