Efficient 3D Segmentation, Registration and Mapping for Mobile Robots

Sometimes simple is better! For certain situations and tasks, simple but robust methods can achieve the same or better results in the same or less time than related sophisticated approaches. In the context of robots operating in real-world environments, key challenges are perceiving objects of interest and obstacles as well as building maps of the environment and localizing therein. The goal of this thesis is to carefully analyze such problem formulations, to deduce valid assumptions and simplifications, and to develop simple solutions that are both robust and fast. All approaches make use of sensors capturing 3D information, such as consumer RGBD cameras. Comparative evaluations show the performance of the developed approaches. For identifying objects and regions of interest in manipulation tasks, a real-time object segmentation pipeline is proposed. It exploits several common assumptions of manipulation tasks such as objects being on horizontal support surfaces (and well separated). It achieves real-time performance by using particularly efficient approximations in the individual processing steps, subsampling the input data where possible, and processing only relevant subsets of the data. The resulting pipeline segments 3D input data with up to 30Hz. In order to obtain complete segmentations of the 3D input data, a second pipeline is proposed that approximates the sampled surface, smooths the underlying data, and segments the smoothed surface into coherent regions belonging to the same geometric primitive. It uses different primitive models and can reliably segment input data into planes, cylinders and spheres. A thorough comparative evaluation shows state-of-the-art performance while computing such segmentations in near real-time. The second part of the thesis addresses the registration of 3D input data, i.e., consistently aligning input captured from different view poses. Several methods are presented for different types of input data. For the particular application of mapping with micro aerial vehicles where the 3D input data is particularly sparse, a pipeline is proposed that uses the same approximate surface reconstruction to exploit the measurement topology and a surface-to-surface registration algorithm that robustly aligns the data. Optimization of the resulting graph of determined view poses then yields globally consistent 3D maps. For sequences of RGBD data this pipeline is extended to include additional subsampling steps and an initial alignment of the data in local windows in the pose graph. In both cases, comparative evaluations show a robust and fast alignment of the input data

Computing fast search heuristics for physics-based mobile robot motion planning

Mobile robots are increasingly being employed to assist responders in search and rescue missions. Robots have to navigate in dangerous areas such as collapsed buildings and hazardous sites, which can be inaccessible to humans. Tele-operating the robots can be stressing for the human operators, which are also overloaded with mission tasks and coordination overhead, so it is important to provide the robot with some degree of autonomy, to lighten up the task for the human operator and also to ensure robot safety. Moving robots around requires reasoning, including interpretation of the environment, spatial reasoning, planning of actions (motion), and execution. This is particularly challenging when the environment is unstructured, and the terrain is \textit{harsh}, i.e. not flat and cluttered with obstacles. Approaches reducing the problem to a 2D path planning problem fall short, and many of those who reason about the problem in 3D don't do it in a complete and exhaustive manner. The approach proposed in this thesis is to use rigid body simulation to obtain a more truthful model of the reality, i.e. of the interaction between the robot and the environment. Such a simulation obeys the laws of physics, takes into account the geometry of the environment, the geometry of the robot, and any dynamic constraints that may be in place. The physics-based motion planning approach by itself is also highly intractable due to the computational load required to perform state propagation combined with the exponential blowup of planning; additionally, there are more technical limitations that disallow us to use things such as state sampling or state steering, which are known to be effective in solving the problem in simpler domains. The proposed solution to this problem is to compute heuristics that can bias the search towards the goal, so as to quickly converge towards the solution. With such a model, the search space is a rich space, which can only contain states which are physically reachable by the robot, and also tells us enough information about the safety of the robot itself. The overall result is that by using this framework the robot engineer has a simpler job of encoding the \textit{domain knowledge} which now consists only of providing the robot geometric model plus any constraints

High Precision Hybrid Pulse and Phase-Shift Laser Ranging System

With the rapid development of military, aerospace, and precision manufacturing technology, a multitude of situations need to carry out a large-range and high-precision distance measurement. The growth of measurement applications has led to a higher requirement for the laser ranging technology which can be accomplished by using different patterns. At present, the pulse laser ranging method is widely used for medium-range and long-range measurement because of the fast measurement speed and considerable measurement range. However, the ranging precision is low. The short-distance measurement mostly adopts the phase-shift laser ranging method which has high ranging accuracy but limited measurement range. Therefore, the research on lifting the accuracy of pulse laser ranging method and extending the measurement range of the phase-shift laser ranging method will be carried out. In this thesis, combining the existing pulse laser ranging system and phase-shift laser ranging system, dual-frequency and single-frequency hybrid pulse and phase-shift laser ranging systems are proposed. The basis for solving the current problems of poor measurement precision in pulse laser ranging method and short measurement distance in phase-shift laser ranging method are provided. Also, the designed structures have a broad application prospect in the fields of industrial production, military, and aviation. At the beginning of the thesis, the principle and characteristics of the current typical laser ranging methods are introduced and analyzed. According to the Fourier Series theory, the spectrum analysis of the pulse signal and the relationship between the pulse signal and the same-frequency sinusoidal signal, the idea of phase-shift laser ranging based on pulse modulation signal is generated. Instead of a continuous sinusoidal signal, the laser is modulated with a periodic pulse signal. Distance measurement by calculating the phase difference on the sinusoidal signal extracted from the pulse signal with the same frequency at the receiving end. Based on the principle of conventional dual-frequency phase-shift laser ranging method, a dual-frequency pulse laser ranging method is proposed. The distance to be measured is obtained by transmitting two periodic pulse signals with different frequency and then combining the implementation of rough and accurate measurement outcomes. Afterward, a single-frequency pulse laser ranging method is introduced. After receiving the pulse signal, the direct counter method is used to realize rough measurement and phase-shift of the co-frequency sinusoidal signal is utilized to improve the ranging accuracy. This proposed model has the advantages of high ranging precision and long-distance measurement without any other auxiliary frequency. The accuracy of the phase difference calculation is the most critical element in both the dual-frequency and single-frequency laser ranging systems. Currently, the commonly used phase difference calculation methods operated in phase-shift laser ranging system are digital synchronous detection, fast Fourier transform method, and all phase fast Fourier transform method. Published works have discussed the performance of frequency estimation and initial phase calculation using these approaches. In this thesis, the precision of phase difference measurement based on these methods above is compared. The effects of normalized frequency deviation, white Gaussian noise, harmonics are simulated in MATLAB. Simulation results show that all phase fast Fourier transform method has a superior anti-noise ability so that exceptional accuracy of phase difference measurement can be achieved. Furthermore, as the number of sampling points increases, all phase fast Fourier transform method will obtain a more accurate calculation consequence. Finally, this thesis carries on the co-simulation test of the designed dual-frequency and single-frequency hybrid pulse and phase-shift laser ranging systems in Optisystem and MATLAB. The transmitting frequencies of pulse signals operated in the dual-frequency method are 15 MHz and 150 KHz. The pulse used in the single-frequency method is set to 15 MHz. In the simulation, the performance of proposed methods is tested by setting various measuring distance. When the number of sampling points is 1024, the standard deviation and ranging error of the dual-frequency method are 3.72 cm and 13.6 cm within 963.15 meters. For the single-frequency method, the results show a 3.78 cm standard deviation and 14.6 cm ranging error. Simulation results illustrate that the proposed ranging methods have lower ranging error compared with recently published works. It means that the combination of the pulse method and the phase-shift method can achieve high-accuracy and long-range measurement