Task planning and control synthesis for robotic manipulation in space applications

Space-based robotic systems for diagnosis, repair and assembly of systems will require new techniques of planning and manipulation to accomplish these complex tasks. Results of work in assembly task representation, discrete task planning, and control synthesis which provide a design environment for flexible assembly systems in manufacturing applications, and which extend to planning of manipulatiuon operations in unstructured environments are summarized. Assembly planning is carried out using the AND/OR graph representation which encompasses all possible partial orders of operations and may be used to plan assembly sequences. Discrete task planning uses the configuration map which facilitates search over a space of discrete operations parameters in sequential operations in order to achieve required goals in the space of bounded configuration sets

The technology base for agile manufacturing

The effective use of information is a critical problem faced by manufacturing organizations that must respond quickly to market changes. As product runs become shorter, rapid and efficient development of product manufacturing facilities becomes crucial to commercial success. Effective information utilization is a key element to successfully meeting these requirements. This paper reviews opportunities for developing technical solutions to information utilization problems within a manufacturing enterprise and outlines a research agenda for solving these problems

Predictive monitoring research: Summary of the PREMON system

Traditional approaches to monitoring are proving inadequate in the face of two important issues: the dynamic adjustment of expectations about sensor values when the behavior of the device is too complex to enumerate beforehand, and the selective but effective interpretation of sensor readings when the number of sensors becomes overwhelming. This system addresses these issues by building an explicit model of a device and applying common-sense theories of physics to model causality in the device. The resulting causal simulation of the device supports planning decisions about how to efficiently yet reliably utilize a limited number of sensors to verify correct operation of the device

Error Detection and Recovery for Robot Motion Planning with Uncertainty

Robots must plan and execute tasks in the presence of uncertainty. Uncertainty arises from sensing errors, control errors, and uncertainty in the geometry of the environment. The last, which is called model error, has received little previous attention. We present a framework for computing motion strategies that are guaranteed to succeed in the presence of all three kinds of uncertainty. The motion strategies comprise sensor-based gross motions, compliant motions, and simple pushing motions

Probability-driven motion planning for mobile robots

This paper proposes a path-planning method for mobile robots in the presence of uncertainty. We analyze environment and control uncertainty and propose methods for incorporating each of them into the planning algorithm. We model the environment using the pyramid structure that encodes the information on occupancy probabilities for each pixel as well as the partial information on conditional probabilities among different pixels. This structure allows for efficient and accurate computation of collision probabilities in the presence of environment uncertainty. The control uncertainty is mainly characterized by its expansion in space and time and is accordingly modeled by a stochastic differential equation that mathematically captures this phenomenon. Models that we develop are inevitably approximate but experiments confirm that they can be used as a reasonable model for motion planning. We have conducted a series of experiments on the mobile platform and some of these results are presented

A Single Differential Equation for First-Excursion Time in a Class of Linear Systems

First-excursion times have been developed extensively in the literature for oscillators; one major application is structural dynamics of buildings. Using the fact that most closed-loop systems operate with a moderate to high damping ratio, we have derived a new procedure for calculating first-excursion times for a class of linear continuous, time-varying systems. In several examples, we show that the algorithm is both accurate and time-efficient. These are important attributes for real-time path planning in stochastic environments, and hence the work should be useful for autonomous robotic systems involving marine and air vehicles.United States. Office of Naval Research (Grant N00014-02-1-0623

An Efficient Path Robustness Metric for Compliant Robots

Many compliant robots suffer from actuation uncertainty. When executing paths, contact with obstacles can lead to the robot becoming unable to continue execution. This paper presents a robustness metric for compliant robots that captures the probability of the robot completing a path, i.e. the probability of avoiding stuck configurations. Our approach constructs a set of reachable C-space volumes between the waypoints of a path. We can then identify stuck configurations within these volumes and approximate their joint pre-image, which we then use to compute the probability of successfully reaching a way-point and subsequently the probability of reaching the path’s goal. We find that our method computes similar robustness predictions to forward simulation more efficiently

Modeling dynamic uncertainty in robot motions

A method for modeling uncertainties that exist in a robotic system, based on stochastic differential equations, is presented. The use of such a model permits the capture in an analytical structure of the ability to properly express uncertainty within the motion descriptions and the dynamic, changing nature of the task and its constraints. With respect to the dynamic nature of robotic motion tasks, the model of the environment uncertainty proposed is dynamic rather than static. The amount of knowledge about the environment is allowed to change as the robot moves. These results suggest that computational models traditionally found in the lower levels in robot systems may have application in the upper planning levels as well. Some experimental results using the model are presented

Towards Reactive Control of Transitional Legged Robot Maneuvers

We propose the idea of a discrete navigation problem – consisting of controlling the state of a discrete-time control system to reach a goal set while in the interim avoiding a set of obstacle states – to approximate a simplified class of transitional legged robotic tasks such as leaping which have no well established mathematical description that lends itself to synthesis. The control relation given in Theorem 1 is (assuming a task solution exists) necessary and sufficient to solve a discrete navigation problem in a minimum number of steps, and is well suited to computation when a legged system’s continuous-time within-stride controller anchors sufficiently simple stance mechanics. We demonstrate the efficacy of this control technique on a physical hopping robot affixed to a boom to reactively leap over an obstacle with a running start, controlling in continuous time during stance to exhibit a linear stance map