Monthly Archives: March 2017

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Implementation of PF SLAM in FPGAs and a good state of the art of the issue

B.G. Sileshi, J. Oliver, R. Toledo, J. Gonçalves, P. Costa, On the behaviour of low cost laser scanners in HW/SW particle filter SLAM applications, Robotics and Autonomous Systems, Volume 80, June 2016, Pages 11-23, ISSN 0921-8890, DOI: 10.1016/j.robot.2016.03.002.

Particle filters (PFs) are computationally intensive sequential Monte Carlo estimation methods with applications in the field of mobile robotics for performing tasks such as tracking, simultaneous localization and mapping (SLAM) and navigation, by dealing with the uncertainties and/or noise generated by the sensors as well as with the intrinsic uncertainties of the environment. However, the application of PFs with an important number of particles has traditionally been difficult to implement in real-time applications due to the huge number of operations they require. This work presents a hardware implementation on FPGA (field programmable gate arrays) of a PF applied to SLAM which aims to accelerate the execution time of the PF algorithm with moderate resource. The presented system is evaluated for different sensors including a low cost Neato XV-11 laser scanner sensor. First the system is validated by post processing data provided by a realistic simulation of a differential robot, equipped with a hacked Neato XV-11 laser scanner, that navigates in the Robot@Factory competition maze. The robot was simulated using SimTwo, which is a realistic simulation software that can support several types of robots. The simulator provides the robot ground truth, odometry and the laser scanner data. Then the proposed solution is further validated on standard laser scanner sensors in complex environments. The results achieved from this study confirmed the possible use of low cost laser scanner for different robotics applications which benefits in several aspects due to its cost and the increased speed provided by the SLAM algorithm running on FPGA.

Interesting approach to deal with the design of complex systems based on analogies with simpler ones

Victor Ragusila, M. Reza Emami, Mechatronics by analogy and application to legged locomotion, Mechatronics, Volume 35, May 2016, Pages 173-191, ISSN 0957-4158, DOI: 10.1016/j.mechatronics.2016.02.007.

A new design methodology for mechatronic systems, dubbed as Mechatronics by Analogy (MbA), is introduced. It argues that by establishing a similarity relation between a complex system and a number of simpler models it is possible to design the former using the analysis and synthesis means developed for the latter. The methodology provides a framework for concurrent engineering of complex systems while maintaining the transparency of the system behavior through making formal analogies between the system and those with more tractable dynamics. The application of the MbA methodology to the design of a monopod robot leg, called the Linkage Leg, is also presented. A series of simulations show that the dynamic behavior of the Linkage Leg is similar to that of a combination of a double pendulum and a spring-loaded inverted pendulum, based on which the system kinematic, dynamic, and control parameters can be designed concurrently.

Real-time trajectory generation for omnidirectional robots, and a good set of basic bibliographical references

Tamás Kalmár-Nagy, Real-time trajectory generation for omni-directional vehicles by constrained dynamic inversion, Mechatronics, Volume 35, May 2016, Pages 44-53, ISSN 0957-4158, DOI: 10.1016/j.mechatronics.2015.12.004.

This paper presents a computationally efficient algorithm for real-time trajectory generation for omni-directional vehicles. The algorithm uses a dynamic inversion based approach that incorporates vehicle dynamics, actuator saturation and bounded acceleration. The algorithm is compared with other trajectory generation algorithms for omni-directional vehicles. The method yields good quality trajectories and is implementable in real-time. Numerical and hardware tests are presented.

Improvements on the ICP algorithm to point cloud registration from a low precision RGB-D sensor

Rogério Yugo Takimoto, Marcos de Sales Guerra Tsuzuki, Renato Vogelaar, Thiago de Castro Martins, André Kubagawa Sato, Yuma Iwao, Toshiyuki Gotoh, Seiichiro Kagei, 3D reconstruction and multiple point cloud registration using a low precision RGB-D sensor, Mechatronics, Volume 35, May 2016, Pages 11-22, ISSN 0957-4158, DOI:j.mechatronics.2015.10.014.

A 3D reconstruction method using feature points is presented and the parameters used to improve the reconstruction are discussed. The precision of the 3D reconstruction is improved by combining point clouds obtained from different viewpoints using structured light. A well-known algorithm for point cloud registration is the ICP (Iterative Closest Point) that determines the rotation and translation that, when applied to one of the point clouds, places both point clouds optimally. The ICP algorithm iteratively executes two main steps: point correspondence determination and registration algorithm. The point correspondence determination is a module that, if not properly executed, can make the ICP converge to a local minimum. To overcome this drawback, two techniques were used. A meaningful set of 3D points using a technique known as SIFT (Scale-invariant feature transform) was obtained and an ICP that uses statistics to generate a dynamic distance and color threshold to the distance allowed between closest points was implemented. The reconstruction precision improvement was implemented using meaningful point clouds and the ICP to increase the number of points in the 3D space. The surface reconstruction is performed using marching cubes and filters to remove the noise and to smooth the surface. The factors that influence the 3D reconstruction precision are here discussed and analyzed. A detailed discussion of the number of frames used by the ICP and the ICP parameters is presented.