To support an Oak Ridge National Laboratory programs exoskeleton project, a unique multi-axis foot force/torque sensor was constructed and tested that has biomedical application such as clinical gait analysis. The challenging aspect of this multi-axis force sensor is that it had to conform to the bending of the human foot, withstand high impact loads, have high force sensitivity, feel comfortable to the human wearer, be integrated into a military style boot, measure the forces on the human foot when either the ball or the heel of the foot is in contact with the ground, respond to both positive and negative loading and have a low overall height and weight. This paper describes the design and testing of this unique sensor.

In typical teleoperated surgeries, skilled staff are still necessary in the remote surgical room to change manipulator tooling and to manage surgical supply delivery and removal. This paper describes the development of a nurse robot to provide automated support to a teleoperated surgical manipulator system in environments where the presence of skilled surgical support staff may not be practical. The tools must be inserted precisely into a compliant manipulator in a timely manner, and the supplies are diverse in nature. To support experimental investigations and evaluations, a seven degrees-of-freedom commercially available manipulator was selected. The design of novel end-effectors, tool grasping and supply holding features, and tool auto-loading systems for optimum surgical tool changing and supply delivery in minimum time is presented. A novel approach for calibration of the nurse robot among compliant and rigid subsystems and for managing forces during subsystem interaction is described and experimental results using this force management approach are presented. Overall experimental performance data for the nurse robot system during tool changing and supply delivery tasks is also presented to illustrate the feasibility of performing these functions in a remote medical or trauma care-assist cell.

The decrease in manpower and increase in material handling needs on many naval vessels provides the motivation to explore the modeling and control of naval robotic and robotic assistive devices. This paper presents a simple methodology to symbolically compute the dynamic equations of motion of a serial link manipulation system operating on the moving deck of a ship. First we provide background information that quantifies the motion of the ship, both in terms of frequency and amplitude. We then formulate the motion of the ship in terms of homogeneous transforms. Likewise, the kinematics of a manipulator is considered as a serial extension of the ship motion. We then show how to use these transforms to formulate the kinetic and potential energy of the arm moving on a ship. As a demonstration, we consider two examples: a one degree-of-freedom system experiencing three sea states operating in a plane to verify the methodology and a 3 degree of freedom system experiencing all six degrees of ship motion to illustrate the ease of computation and complexity of the solution. We provide a preliminary comparison between conventional linear control and repetitive learning control (RLC) and show how fixed time delay RLC breaks down due to the varying wave disturbance frequency.

The efficient utilization of the motion capabilities of mobile manipulators, i.e. manipulators mounted on mobile platforms, requires the resolution of the kinematically redundant system formed by the addition of the degrees of freedom (DOF) of the platform to those of the manipulator. At the velocity level, the linearized Jacobian equation for such a redundant system represents an underspecified system of algebraic equations, which can be subject to a set of constraints such as obstacles in the workspace and various limits on the joint motions. A method, which we named the FSP, has been developed to resolve such underspecified systems with constraints that may vary in time and in number during a single trajectory. The application of the method to motion planning problems with obstacle and joint limit avoidance was discussed in some of our previous work. In this paper, we present the treatment in the FSP of a non-holonomic constraint on the platform motion, and give corresponding analytical solutions for resolving the redundancy with a general optimization criterion. Comparative trajectories involving a 10 DOF mobile manipulator testbed moving with and without a non-holonomic constraint for the platform motion, are presented to illustrate the use and efficiency of the FSP approach in motion planning problems for highly kinematically redundant and constrained systems.

A new method for mitigating unexpected impact of a redundant manipulator with an object in its environment is presented. Kinematic constraints are utilized with the recently developed method known as full space parameterization (FSP). System performance criteria and constraints are changed at impact to return the end effector to the point of impact and halt the arm. Since large joint accelerations could occur as the manipulator is halted joint acceleration bounds are imposed to simulate physical actuator limitations. Simulation results are presented for the case of a simple redundant planar manipulator.

A solution method is presented for the motion planning and control of kinematically redundant serial-link manipulators in the presence of motion constraints such as joint limits or obstacles. Given a trajectory for the end-effector, the approach utilizes the recently proposed full space parameterization (FSP) method to generate a parameterized expression for the entire space of solutions of the unconstrained system. At each time step, a constrained optimization technique is then used to analytically find the specific joint motion solution that satisfies the desired task objective and all the constraints active during the time step. The method is applicable to systems operating in a priori known environments or in unknown environments with sensor-based obstacle detection. The derivation of the analytical solution is first presented for a general type of kinematic constraint and is then applied to the problem of motion planning for redundant manipulators with joint limits and obstacle avoidance. Sample results using planar and 3D manipulators with various degrees of redundancy are presented to illustrate the efficiency and wide applicability of constrained motion planning using the FSP approach.

A new analytical method to resolve underspecified systems of algebraic equations is presented. The method is referred to as the full space parameterization (FSP) method and utilizes easily-calculated projected solution vectors to generate the entire space of solutions of the underspecified system. Analytic parameterizations for both the space of solutions and the null space of the system reduce the determination of a task-requirement-based single solution to a m-n dimensional problem, where m-n is the degree of underspecification, or degree of redundancy, of the system. An analytical solution is presented to directly calculate the least-norm solution from the parameterized space and the results are compared to solutions of the standard pseudo-inverse algorithm which embodies the (least-norm) Moore-Penrose generalized inverse. Application of the new solution method to a variety of systems and task requirements are discussed, and sample results using four-link planar manipulators with one or two degrees of redundancy and a seven degree-of-freedom manipulator with one or four degrees of redundancy are presented to illustrate the efficiency of the new FSP method and algorithm.>

An important characteristic of mobile manipulators is their particular kinematic redundancy created by the addition of the degrees of freedom of the platform and those of the manipulator. This kinematic redundancy is very desirable since it allows mobile manipulators to operate under many modes of motion and to perform a wide variety of tasks. On the other hand, it also significantly complicates the problem of planning a series of sequential tasks, in particular for the critical times at which the system needs to "switch" from one task to the other (task commutation), with changes in mode of motion, task requirement, and task constraints. This paper focuses on the problem of planning the positions and configurations in which the system needs to be at task commutation in order to assure that it can properly initiate the next task to be performed. The concept of and need for "commutation configurations" in sequences of mobile manipulator tasks is introduced, and an optimization approach is proposed for their calculation during the task sequence planning phase. A variety of optimization criteria were previously investigated to optimize the task commutation configurations of the system when task requirements involve obstacle avoidance, reach, maneuverability, and optimization of strength. In this paper, the authors show that a "minimax" approach is particularly adapted for most of these requirements. The authors develop the corresponding criteria and discuss solution algorithms to solve the "minimax" optimization problems. An implementation of the algorithms for the authors' HERMIES-III mobile manipulator is then described and sample results are presented and discussed.>

This paper presents the concepts for a new family of holonomic wheeled platforms that feature full omnidirectionality with simultaneous and independently controlled rotational and translational motion capabilities. The authors first present the "orthogonal-wheels" concept and the two major wheel assemblies on which these platforms are based. The authors then describe how a combination of these assemblies with appropriate control can be used to generate an omnidirectional capability for mobile robot platforms. Several alternative designs are considered, and their respective characteristics with respect to rotational and translational motion control are discussed. The design and control of a prototype platform developed to test and demonstrate the proposed concepts is then described, and experimental results illustrating the full omnidirectionality of the platform with decoupled rotational and translational degrees of freedom are presented.>

The authors present the concepts for a new family of wheeled platforms which feature full omnidirectionality with simultaneous and independent rotational and translational motion capabilities. They first describe the original orthogonal-wheels assembly on which these platforms are based and discuss how a combination of these assemblies is used to generate an omnidirectional capability. The design and control of a prototype platform developed to test and demonstrate the proposed concepts are then described, and experimental results illustrating the full omnidirectionality of the platform with decoupled rotational and translational degrees of freedom are presented.>

Two types of computer boards including custom-designed VLSI chips have been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The design and operation of these boards are first described, and an example of their use for the autonomous navigation of a mobile robot is presented. The development of qualitative reasoning schemes emulating human-like navigation in a priori unknown environments is discussed. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse and inaccurate sensor data.>

An approach merging the concepts of fuzzy logic and sensor-based behaviors has been developed to add a qualitative reasoning capability to the real-time control of autonomous mobile robots. The approach is implemented using custom-designed computer boards which include recently developed VLSI fuzzy inferencing chips. The design and operation of these boards are first described and an example of their use for the autonomous navigation of a mobile robot is presented. The development of qualitative reasoning schemes emulating human- like navigation in a-priori unknown environments is discussed. The approach using superposition of elemental sensor-based behaviors expressed in the fizzy Sets theoretic framework is shown to allow easy development and testing of the inferencing rule base, while providing for progressive addition of behaviors to resolve situations of increasing complexity. The efficiency of such schemes, which can consist of as little as a dozen qualitative rules, is illustrated in experiments involving an autonomous mobile robot navigating on the basis of very sparse and inaccurate sensor data.

A method for rapidly computing the possible maneuvers of car-like robots within convex polygonal cells is presented. In a convex polygonal cell, maneuvering can be completely handled with geometric reasoning, and, since only a few boundary configurations have to be checked to avoid collision, the method allows precise computation of the maneuvers without using the whole configuration space. General environments are then described by means of a graph connecting overlapping convex cells. To find a path to a goal, the graph is searched to determine the cells that have to be traversed. Intermediate configurations are then computed inside the intersection of each pair of adjacent cells. Finally, the trajectories generated inside each cell are assembled to produce global collision-free paths in complex environments.>

Recent work toward the development of low-complexity, sensor-based inferencing methods to serve as the initial links of incremental robotic learning systems is described. A multimodal learning approach is proposed in which distributed sensory sources are used to both trigger the observation of and perceive relevant learning instances in a human-robot synergistic framework. Three components of the incremental learning system for the CESARm advanced manipulator testbed are presented that encompass the learning of objects and work area characteristics through the triggering of attention and rote learning, the learning of elemental manipulation tasks by observation of human actions, and the self-assessment of acquired skills and learned knowledge through task performance evaluation. Feasibility experiments with each of these three learning methodologies are presented, and some results are discussed.>

In applications of robotics to surveillance and mapping at nuclear facilities the scene to be described is three-dimensional. Using range data a 3-D model of the environment can be built. First, each measured point on the object surface is surrounded by a solid sphere with a radius determined by the range to that point. Then the 3-D shapes of the visible surfaces are obtained by taking the (Boolean) union of the spheres. Using this representation distances to boundary surfaces can be efficiently calculated. This feature is particularly useful for navigation purposes. The efficiency of the proposed approach is illustrated by a simulation of a spherical robot navigating in a 3-D room with static obstacles.