Are counterfactuals with true antecedents and consequents automatically true? That is, is Conjunction Conditionalization: (X ∧ Y) ⊃ (X > Y) valid? Stalnaker and Lewis think so, but many others disagree. We note here that the extant arguments for Conjunction Conditionalization are unpersuasive, before presenting a family of more compelling arguments. These arguments rely on some standard theorems of the logic of counterfactuals as well as a plausible and popular semantic claim about certain semifactuals. Denying Conjunction Conditionalization, then, requires rejecting other aspects of the standard logic of counterfactuals or else our intuitive picture of semifactuals.

The mean weight of a cycle in an edge-weighted graph is the sum of the cycle's edge weights divided by the cycle's length. We study the minimum mean-weight cycle on the complete graph on n vertices, with random i.i.d. edge weights drawn from an exponential distribution with mean 1. We show that the probability of the min mean weight being at most c/n tends to a limiting function of c which is analytic for c ≤ 1/e, discontinuous at c = 1/e, and equal to 1 for c > 1/e. We further show that if the min mean weight is ≤ 1/(en), then the length of the relevant cycle is Θp(1) (i.e., it has a limiting probability distribution which does not scale with n), but that if the min mean weight is > 1/(en), then the relevant cycle almost always has mean weight (1 + o(1))/(en) and length at least (2/π2 − o (1)) log2n log log n.

In this paper, a kinematic model of a dual-arm/hand robotic system is derived, which allows the computation of the object position and orientation from the joint variables of each arm and each finger as well as from a suitable set of contact variables. On the basis of this model, a motion planner is designed, where the kinematic redundancy of the system is exploited to satisfy some secondary tasks aimed at ensuring grasp stability and manipulation dexterity without violating physical constraints. To this purpose, a prioritized task sequencing with smooth transitions between tasks is adopted. Afterwards, a controller is designed so as to execute the motion references provided by the planner and, at the same time, achieve a desired contact force exerted by each finger on the grasped object. To this end, a parallel position/force control is considered. A simulation case study has been developed by using the dynamic simulator GRASPIT!, which has been suitably adapted and redistributed.

In this paper, human viscosity perception in haptic teleoperation systems is thoroughly analyzed. An accurate perception of viscoelastic environmental properties such as viscosity is a critical ability in several contexts, such as telesurgery, telerehabilitation, telemedicine, and soft-tissue interaction. We study and compare the ability to perceive viscosity from the standpoint of detection and discrimination using several relevant control methods for the teleoperator. The perception-based method, which was proposed by the authors to enhance the operator's kinesthetic perception, is compared with the conventional transparency-based control method for the teleoperation system. The fidelity-based method, which is a primary method among perception-centered control schemes in teleoperation, is also studied. We also examine the necessity and impact of the remote-site force information for each of the methods. The comparison is based on a series of psychophysical experiments measuring absolute threshold and just noticeable difference for all conditions. The results clearly show that the perception-based method enhances both detection and discrimination abilities compare with other control methods. The results further show that the fidelity-based method confers a better discrimination ability than the transparency-based method, although this is not true with respect to detection ability. In addition, we show that force information improves viscosity detection for all control methods, as predicted from previous theoretical analysis, but improves the discrimination threshold only for the perception-based method.

An autonomous robot must obtain information about its surroundings to accomplish multiple tasks that are greatly improved when this information is efficiently incorporated into a map. Some examples are navigation, manipulation, localization, etc. This mapping problem has been an important research area in mobile robotics during last decades. It does not have a unique solution and can be divided into multiple sub-problems. Two different aspects of the mobile robot mapping problem are addressed in this work. First, we have developed a Differential Evolution-based scan matching algorithm that operates with high accuracy in three-dimensional environments. The map obtained by an autonomous robot must be consistent after registration. It is basic to detect when the robot is navigating around a previously visited place in order to minimize the accumulated error. This phase, which is called loop detection, is the second aspect studied here. We have developed an algorithm that extracts the most important features from two different three-dimensional laser scans in order to obtain a loop indicator that is used to detect when the robot is visiting a known place. This approach allows the introduction of very different characteristics in the descriptor. First, the surface features include the geometric forms of the scan (lines, planes, and spheres). Second, the numerical features are values that describe several numerical properties of the measurements: volume, average range, curvature, etc. Both algorithms have been tested with real data to demonstrate that these are efficient tools to be used in mapping tasks.

The increased use of unmanned aerial vehicles (UAVs) is coincidentally accompanied by a notable lack of sensors suitable for enabling further improvement in levels of autonomy and, consequently, integration into the National Airspace System (NAS). The majority of available sensors suitable for UAV integration into the NAS are based on infrared detectors, focal plane arrays, optical and ultrasonic rangefinders, etc. These sensors are generally not able to detect or identify other UAV-sized targets and, when detection is possible, considerable computational power is typically required for successful identification. Furthermore, the performance of visual-range optical sensor systems may suffer when operating under conditions that are typically encountered during search and rescue, surveillance, combat, and most other common UAV applications. However, the addition of a miniature RADAR sensor can, in consort with other sensors, provide comprehensive target detection and identification capabilities for UAVs. This trend is observed in manned aviation where RADAR sensors are the primary on-board detection and identification sensors. In this paper, a miniature, lightweight X-band RADAR sensor for use on a miniature (710-mm rotor diameter) rotorcraft is described. We present an analysis of the performance of the RADAR sensor in a realistic scenario with two UAVs. Additionally, an analysis of UAV navigation and collision avoidance behaviors is performed to determine the effect of integrating RADAR sensors into UAVs. Further study is also performed to demonstrate the scalability of the RADAR for use with larger UAV classes.

In this paper, a vision-based scheme for the autonomous hovering of a miniature quad-rotor is developed. Cameras are used to estimate the position and the translational velocity of the vehicle. The dynamic model of the miniature quad-rotor is developed using the Newton–Euler approach. A nonlinear controller based on a separated saturation control strategy for a miniature quad-rotor is presented. To validate the theoretical results, an embedded control system for the miniature quad-rotor has been developed. Thus, the analytic results are supported by experimental tests. Experimental results have validated the proposed control strategy.

In this paper an optimal path planning method based on a new evolutionary algorithm is presented for higher order robotic systems. It is a combination of immune system and wavelet mutation. By increasing the system's dimensions, the complexity of algorithm grows linearly. The obtained results have been compared with other optimal path producing algorithms, and its excellence in terms of optimality has been proved. Strengths of this method are simplicity in large-scale path planning, being free of most of the common deadlocks in usual method, and ability to obtain more optimized results than other similar methods. The effectiveness of this approach on simulation case studies for a three-link planar robot and 5 degrees of freedom mobile manipulators as well as an experiment for a mobile robot called K-joniour is shown.

This paper deals with the problem of the practical tracking control of an experimental car-like system called the Robucar. The car-like Robucar is a four-wheeled car in a single steering mode. Based on a kinematic model of the car-like Robucar, a practical tracking controller is designed using the second-order sliding mode control of the super twisting algorithm. Hence, the output tracking of the desired trajectory is achieved, and the tracking errors vanish asymptotically. Experimental tests on the car-like Robucar are presented for simple and real-time nonholonomic trajectories, and comparative results with the conventional sliding controller demonstrate the applicability and efficiency of the proposed controller.