Abstract
This paper presents an algorithm capable of generating smooth, feasible paths for an any-shape non-holonomic mobile robot, taking into account orientation restrictions, with the aim of navigating close to obstacles. Our contribution consists in an extension of the A* algorithm in a cell decomposition, where besides its position, the orientation of the platform is also considered when searching for a path. This is achieved by constructing 16 layers of orientations and only visiting neighbor layers when searching for the lowest cost. To simplify collision checking, the robot's footprint is used to inflate obstacles, yet, to allow the robot to find paths close to obstacles, the actual footprint of the robot must used. By discretizing the orientation space into layers and computing an oriented footprint for each layer, the actual footprint of the robot is used, increasing the configuration space without becoming computationally expensive. The path planning algorithm was developed under the EU-funded project CARLoS(1) and was implemented in a stud welding robot simulated within a naval industry environment, validating our approach.

Abstract
The simulation of a robot with a high number of joints can easily become unstable. Numerical errors on the first joint of the chain are propagated to the other joints. This is a very common problem in humanoid robots. A way to plan the gait for these robots is using simulation and optimization techniques. This paper addresses a new approach to optimizing gait parameter sets using an adaptive simulated annealing optimization algorithm, combined with a new joint model that reduces its instability. The new model and the optimization are implemented in SimTwo (a developed physical robot simulator that is capable of simulating user defined robots in a three-dimensional space, since it includes a physical model based on rigid body dynamics) and results are shown that validate the approach.

Abstract
There are several approaches to create the Humanoid robot gait planning. This problem presents a large number of unknown parameters that should be found to make the humanoid robot to walk. Optimization in simulation models can be used to find the gait based on several criteria such as energy minimization, acceleration, step length among the others. The presented paper addresses a comparison between two optimization methods, the Stretched Simulated Annealing and the Genetic Algorithm, that runs in an accurate and stable simulation model. Final results show the comparative study and demonstrate that optimization is a valid gait planning technique.

Abstract
A laser scanner is a popular sensor widely used in industry and mobile robots applications that measures the distance to the sensor on a slice of the plan. At the same time, simulation has becoming more and more used in industries and academia since it presents several advantages. It takes the building and rebuilding phase out of the loop by using the model already created in the design phase. Further, simulation time on testing is cheaper and faster than performing the multiple tests of the design each time. Besides, it is easier to measure some variables in simulation than in real scenarios. In this paper, a laser scanner sensor is modeled and implemented in a developed simulator that already has several other sensors and actuators models. The presented simulation reflects the laser model properties such as target color dependences, noise, limits, time constraints, and target angle functions. As a case study, the same scenario is assembled with real components on a conveyer belt and in simulation. Results from both approaches are compared and validate the proposed model methodology. As an example, a 3D object recognition task is addressed highlighting the developed realistic model. Further industrial and R&D implementations based on this sensor could be stressed in simulation before implementation. © Springer International Publishing Switzerland 2013.

Abstract
This paper describes the EMG30 mechanical and electrical modeling and its simulation resorting to SimTwo (Robot@Factory mobile robot competition official simulator). It is described the developed setup applied to obtain the experimental data that was used to estimate the actuator parameters. It was obtained an electro-mechanical dynamical model that describes the motor, its gear box, and the encoder. The motivation to model and simulate the EMG30 is the fact that it is an actuator worldwide popular in the mobile robotics domain, being a low cost 12v motor equipped with encoders and a 30:1 reduction gearbox. The Goal of this work is to provide more realism and new features to the Robot@Factory official simulator, allowing participating teams to produce and validate different robot prototypes and its software, reducing considerably the development time. © Springer International Publishing Switzerland 2013.

Abstract
Industrial laser cutting machines use a type of support base that sometimes causes the cut metal parts to tilt or fall, which hinders the robot from picking the parts after cutting. The objective of this work is to calculate the 3D orientation of these metal parts with relation to the main metal sheet to successfully perform the subsequent robotic pick-and-place operation. For the perception part the system relies on the low cost 3D sensing Microsoft Kinect, which is responsible for mapping the environment. The previously known part positions are mapped in the new environment and then a plane fitting algorithm is applied to obtain its 3D orientation. The implemented algorithm is able to detect if the piece has fallen or not. If not, the algorithm calculates the orientation of each piece separately. This information is later used for the robot manipulator to perform the pick-and-place operation with the correct tool orientation. This makes it possible to automate a manufacturing process that is entirely human dependent nowadays.