Robust hybrid control for autonomous vehicle motion planning

Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2001.Includes bibliographical references (p. 141-150).This dissertation focuses on the problem of motion planning for agile autonomous vehicles. In realistic situations, the motion planning problem must be solved in real-time, in a dynamic and uncertain environment. The fulfillment of the mission objectives might also require the exploitation of the full maneuvering capabilities of the vehicle. The main contribution of the dissertation is the development of a new computational and modelling framework (the Maneuver Automaton), and related algorithms, for steering underactuated, nonholonomic mechanical systems. The proposed approach is based on a quantization of the system's dynamics, by which the feasible nominal system trajectories are restricted to the family of curves that can be obtained by the interconnection of suitably defined primitives. This can be seen as a formalization of the concept of "maneuver", allowing for the construction of a framework amenable to mathematical programming. This motion planning framework is applicable to all time-invariant dynamical systems which admit dynamic symmetries and relative equilibria. No other assumptions are made on the dynamics, thus resulting in exact motion planning techniques of general applicability. Building on a relatively expensive off-line computation phase, we provide algorithms viable for real-time applications. A fundamental advantage of this approach is the ability to provide a mathematical foundation for generating a provably stable and consistent hierarchical system, and for developing the tools to analyze the robustness of the system in the presence of uncertainty and/or disturbances.(cont.) In the second part of the dissertation, a randomized algorithm is proposed for real-time motion planning in a dynamic environment. By employing the optimal control solution in a free space developed for the maneuver automaton (or for any other general system), we present a motion planning algorithm with probabilistic convergence and performance guarantees, and hard safety guarantees, even in the face of finite computation times. The proposed methodologies are applicable to a very large class of autonomous vehicles: throughout the dissertation, examples, simulation and experimental results are presented and discussed, involving a variety of mechanical systems, ranging from simple academic examples and laboratory setups, to detailed models of small autonomous helicopters.by Emilio Frazzoli.Ph.D

Robotic manipulators for in situ inspections of jet engines

Jet engines need to be inspected periodically and, in some instances, repaired. Currently, some of these maintenance operations require the engine to be removed from the wing and dismantled, which has a significant associated cost. The capability of performing some of these inspections and repairs while the engine is on-wing could lead to important cost savings. However, existing technology for on-wing operations is limited, and does not suffice to satisfy some of the needs. In this work, the problem of performing on-wing operations such as inspection and repair is analysed, and after an extensive literature review, a novel robotic system for the on-wing insertion and deployment of probes or other tools is proposed. The system consists of a fine-positioner, which is a miniature and dexterous robotic manipulator; a gross-positioner, which is a device to insert the fine-positioner to the engine region of interest; an end-effector, such as a probe; a deployment mechanism, which is a passive device to ensure correct contact between probe and component; and a feedback system that provides information about the robot state for control. The research and development work conducted to address the main challenges to create this robotic system is presented in this thesis. The work is focussed on the fine-positioner, as it is the most relevant and complex part of the system. After a literature review of relevant work, and as part of the exploration of potential robot concepts for the system, the kinematic capabilities of concentric tube robots (CTRs) are first investigated. The complete set of stable trajectories that can be traced in follow-the-leader motion is discovered. A case study involving simulations and an experiment is then presented to showcase and verify the work. The research findings indicate that CTRs are not suitable for the fine-positioner. However, they show that CTRs with non-annular cross section can be used for the gross-positioner. In addition, the new trajectories discovered show promise in minimally invasive surgery (MIS). Soft robotic manipulators with fluidic actuation are then selected as the most suitable concept for the fine-positioner. The design of soft robotic manipulators with fluidic actuation is investigated from a general perspective. A general framework for the design of these devices is proposed, and a set of design principles are derived. These principles are first applied in a MIS case study to illustrate and verify the work. Finite element (FE) simulations are then reported to perform design optimisation, and thus complete the case study. The design study is then applied to determine the most suitable design for the fine-positioner. An additional analytical derivation is developed, followed by FE simulations, which extend those of the case study. Eventually, this work yields a final design of the fine-positioner. The final design found is different from existing ones, and is shown to provide an important performance improvement with respect to existing soft robots in terms of wrenches it can support. The control of soft and continuum robots relevant to the fine-positioner is also studied. The full kinematics of continuum robots with constant curvature bending and extending capabilities are first investigated, which correspond to a preliminary design concept conceived for the fine-positioner. Closed-form solutions are derived, closing an open problem. These kinematics, however, do not exactly match the final fine-positioner design selected. Thus, an alternative control approach based on closed-loop control laws is then adopted. For this, a mechanical model is first developed. Closed-loop control laws are then derived based on this mechanical model for planar operation of a segment of the fine-positioner. The control laws obtained represent the foundation for the subsequent development of control laws for a full fine-positioner operating in 3D. Furthermore, work on path planning for nonholonomic systems is also reported, and a new algorithm is presented, which can be applied for the insertion of the overall robotic system. Solutions to the other parts of the robotic system for on-wing operations are also reported. A gross-positioner consisting of a non-annular CTR is proposed. Solutions for a deployment mechanism are also presented. Potential feedback systems are outlined. In addition, methods for the fabrication of the systems are reported, and the electronics and systems required for the assembly of the different parts are described. Finally, the use of the robotic system to perform on-wing inspections in a representative case study is studied to determine the viability. Inspection strategies are shortlisted, and simulations and experiments are used to study them. The results, however, indicate that inspection is not viable since the signal to noise ratio is excessively low. Nonetheless, the robotic system proposed, and the research conducted, are still expected to be useful to perform a range of on-wing operations that require the insertion and deployment of a probe or other end-effector. In addition, the trajectories discovered for CTRs, the design found for the fine-positioner, and the advances on control, also have significant potential in MIS, where there is an important need for miniature robotic manipulators and similar devices.Open Acces

Decentralized path planning for multiple agents in complex environments using rapidly-exploring random trees

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 89-94).This thesis presents a novel approach to address the challenge of planning paths for real-world multi-agent systems operating in complex environments. The technique developed, the Decentralized Multi-Agent Rapidly-exploring Random Tree (DMARRT) algorithm, is an extension of the CL-RRT algorithm to the multi-agent case, retaining its ability to plan quickly even with complex constraints. Moreover, a merit-based token passing coordination strategy is also presented as a core component of the DMA-RRT algorithm. This coordination strategy makes use of the tree of feasible trajectories grown in the CL-RRT algorithm to dynamically update the order in which agents plan. This reordering is based on a measure of each agent's incentive to replan and allows agents with a greater incentive to plan sooner, thus reducing the global cost and improving the team's overall performance. An extended version of the algorithm, Cooperative DMA-RRT, is also presented to introduce cooperation between agents during the path selection process. The paths generated are proven to satisfy inter-agent constraints, such as collision avoidance, and a set of simulation and experimental results verify the algorithm's performance. A small scale rover is also presented as part of a practical test platform for the DMA-RRT algorithm.by Vishnu R. Desaraju.S.M

Improving Leader-Follower Formation Control Performance for Quadrotors

This thesis aims to improve the leader-follower team formation flight performance of Unmanned Aerial Vehicles (UAVs) by applying nonlinear robust and optimal techniques, in particular the nonlinear H_infinity and the iterative Linear Quadratic Regulator (iLQR), to stabilisation, path tracking and leader-follower team formation control problems. Existing solutions for stabilisation, path tracking and leader-follower team formation control have addressed a linear or nonlinear control technique for a linearised system with limited disturbance consideration, or for a nonlinear system with an obstacle-free environment. To cover part of this area of research, in this thesis, some nonlinear terms were included in the quadrotors' dynamic model, and external disturbance and model parameter uncertainties were considered. Five different controllers were developed. The first and the second controllers, the nonlinear suboptimal H_infinity control technique and the Integral Backstepping (IBS) controller, were based on Lyapunov theory. The H_infinity controller was developed with consideration of external disturbance and model parameter uncertainties. These two controllers were compared for path tracking and leader-follower team formation control. The third controller was the Proportional Derivative square (PD2), which was applied for attitude control and compared with the H_infinity controller. The fourth and the fifth controllers were the Linear Quadratic Regulator (LQR) control technique and the optimal iLQR, which was developed based on the LQR control technique. These were applied for attitude, path tracking and team formation control and there results were compared. Two features regarding the choice of the control technique were addressed: stability and robustness on the one hand, which were guaranteed using the H_infinity control technique as the disturbance is inherent in its mathematical model, and the improvement in the performance optimisation on the other, which was achieved using the iLQR technique as it is based on the optimal LQR control technique. Moreover, one loop control scheme was used to control each vehicle when these controllers were implemented and a distributed control scheme was proposed for the leader-follower team formation problem. Each of the above mentioned controllers was tested and verified in simulation for different predefined paths. Then only the nonlinear H_infinity controller was tested in both simulation and real vehicles experiments