The power dissipation method and kinematic reducibility of multiple-model robotic systems

This paper develops a formal connection between the power dissipation method (PDM) and Lagrangian mechanics, with specific application to robotic systems. Such a connection is necessary for understanding how some of the successes in motion planning and stabilization for smooth kinematic robotic systems can be extended to systems with frictional interactions and overconstrained systems. We establish this connection using the idea of a multiple-model system, and then show that multiple-model systems arise naturally in a number of instances, including those arising in cases traditionally addressed using the PDM. We then give necessary and sufficient conditions for a dynamic multiple-model system to be reducible to a kinematic multiple-model system. We use this result to show that solutions to the PDM are actually kinematic reductions of solutions to the Euler-Lagrange equations. We are particularly motivated by mechanical systems undergoing multiple intermittent frictional contacts, such as distributed manipulators, overconstrained wheeled vehicles, and objects that are manipulated by grasping or pushing. Examples illustrate how these results can provide insight into the analysis and control of physical systems

Kinematic reducibility of multiple model systems

This paper considers the relationship between second order multiple model systems and first order multiple model systems. Such a relationship is important to, among other things, studying path planning for mechanical control systems. This is largely due to the fact that the computational complexity of a path planning problem rapidly increases with the dimension of the state space, implying that being able to reduce a path planning problem from TQ to Q can be helpful. Not surprisingly, the necessary and sufficient condition for such a reduction is that each model constituting a multiple model control system be reducible. We present an extensive example in order to illustrate how these results can provide insight into the control of some specific physical systems

Control of multiple model systems

This thesis considers the control of multiple model systems. These are systems for which only one model out of some finite set of models gives the system dynamics at any given time. In particular, the model that gives the system dynamics can change over time. This thesis covers some of the theoretical aspects of these systems, including controllability and stabilizability. As an application, ``overconstrained' mechanical systems are modeled as multiple model systems. Examples of such systems include distributed manipulation problems such as microelectromechanical systems and many wheeled vehicles such as the Sojourner vehicle of the Mars Pathfinder mission. Such systems are typified by having more Pfaffian constraints than degrees of freedom. Conventional classical motion planning and control theories do not directly apply to overconstrained systems. Control issues for two examples are specifically addressed. The first example is distributed manipulation. Distributed manipulation systems control an object's motion through contact with a high number of actuators. Stability results are shown for such systems and control schemes based on these results are implemented on a distributed manipulation test-bed. The second example is that of overconstrained vehicles, of which the Mars rover is an example. The nonlinear controllability test for multiple model systems is used to answer whether a kinematic model of the rover is or is not controllable

NASA patent abstracts bibliography: A continuing bibliography. Section 1: Abstracts (supplement 43)

Abstracts are provided for 128 patents and patent applications entered into the NASA scientific and technical information system during the period Jan. 1993 through Jun. 1993. Each entry consists of a citation, an abstract, and in most cases, a key illustration selected from the patent or patent application

Axel Rover Tethered Dynamics and Motion Planning on Extreme Planetary Terrain

Some of the most appealing science targets for future exploration missions in our solar system lie in terrains that are inaccessible to state-of-the-art robotic rovers such as NASA's Opportunity, thereby precluding in situ analysis of these rich opportunities. Examples of potential high-yield science areas on Mars include young gullies on sloped terrains, exposed layers of bedrock in the Victoria Crater, sources of methane gas near Martian volcanic ranges, and stepped delta formations in heavily cratered regions. In addition, a recently discovered cryovolcano on Titan and frozen water near the south pole of our own Moon could provide a wealth of knowledge to any robotic explorer capable of accessing these regions. To address the challenge of extreme terrain exploration, this dissertation presents the Axel rover, a two-wheeled tethered robot capable of rappelling down steep slopes and traversing rocky terrain. Axel is part of a family of reconfigurable rovers, which, when docked, form a four-wheeled vehicle nicknamed DuAxel. DuAxel provides untethered mobility to regions of extreme terrain and serves as an anchor support for a single Axel when it undocks and rappels into low-ground. Axel's performance on extreme terrain is primarily governed by three key system components: wheel design, tether control, and intelligent planning around obstacles. Investigations in wheel design and optimizing for extreme terrain resulted in the development of grouser wheels. Experiments demonstrated that these grouser wheels were very effective at surmounting obstacles, climbing rocks up to 90% of the wheel diameter. Terramechanics models supported by experiments showed that these wheels would not sink excessively or become trapped in deformable terrain. Predicting tether forces in different configurations is also essential to the rover's mobility. Providing power, communication, and mobility forces, the tether is Axel's lifeline while it rappels steep slopes, and a cut, abraded, or ruptured tether would result in an untimely end to the rover's mission. Understanding tether forces are therefore paramount, and this thesis both models and measures tension forces to predict and avoid high-stress scenarios. Finally, incorporating autonomy into Axel is a unique challenge due to the complications that arise during tether management. Without intelligent planning, rappelling systems can easily become entangled around obstacles and suffer catastrophic failures. This motivates the development of a novel tethered planning algorithm, presented in this thesis, which is unique for rappelling systems. Recent field experiments in natural extreme terrains on Earth demonstrate the Axel rover's potential as a candidate for future space operations. Both DuAxel and its rappelling counterpart are rigorously tested on a 20 meter escarpment and in the Arizona desert. Through analysis and experiments, this thesis provides the framework for a new generation of robotic explorers capable of accessing extreme planetary regions and potentially providing clues for life beyond Earth.</p

Monitoring using Heterogeneous Autonomous Agents.

This dissertation studies problems involving different types of autonomous agents observing objects of interests in an area. Three types of agents are considered: mobile agents, stationary agents, and marsupial agents, i.e., agents capable of deploying other agents or being deployed themselves. Objects can be mobile or stationary. The problem of a mobile agent without fuel constraints revisiting stationary objects is formulated. Visits to objects are dictated by revisit deadlines, i.e., the maximum time that can elapse between two visits to the same object. The problem is shown to be NP-complete and heuristics are provided to generate paths for the agent. Almost periodic paths are proven to exist. The efficacy of the heuristics is shown through simulation. A variant of the problem where the agent has a finite fuel capacity and purchases fuel is treated. Almost periodic solutions to this problem are also shown to exist and an algorithm to compute the minimal cost path is provided. A problem where mobile and stationary agents cooperate to track a mobile object is formulated, shown to be NP-hard, and a heuristic is given to compute paths for the mobile agents. Optimal configurations for the stationary agents are then studied. Several methods are provided to optimally place the stationary agents; these methods are the maximization of Fisher information, the minimization of the probability of misclassification, and the minimization of the penalty incurred by the placement. A method to compute optimal revisit deadlines for the stationary agents is given. The placement methods are compared and their effectiveness shown using numerical results. The problem of two marsupial agents, one carrier and one passenger, performing a general monitoring task using a constrained optimization formulation is stated. Necessary conditions for optimal paths are provided for cases accounting for constrained release of the passenger, termination conditions for the task, as well as retrieval and constrained retrieval of the passenger. A problem involving two marsupial agents collecting information about a stationary object while avoiding detection is then formulated. Necessary conditions for optimal paths are provided and rectilinear motion is demonstrated to be optimal for both agents.PhDAerospace EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/111439/1/jfargeas_1.pd