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Nomad, an open architecture motion controller, is described. It is formed by a combination of TMOS, C-WORKS, and other utilities. Nomad software runs in a UNIX environment and provides for sensor-controlled robotic motions, with user replaceable kinematics. It can also be tailored for highly specialized applications. Open controllers such as Nomad should have a major impact on the robotics industry.
This paper illustrates the application of symbolic computation in connection with three aspects of mechanical systems: (1) The derivation of dynamical equations by Lagrangian methods; (2) The analysis and synthesis of kinematic mechanisms; and (3) A robot manipulator arm.
The Serpentine Robot is a prototype hyper-redundant (snake-like) manipulator system developed at the Jet Propulsion Laboratory. It is designed to navigate and perform tasks in obstructed and constrained environments in which conventional 6 DOF manipulators cannot function. Described are the robot mechanical design, a joint assembly low level inverse kinematic algorithm, control development, and applications.
A robotic benchmark problem useful for evaluating alternative neural network controllers is presented. Specifically, it derives two camera models and the kinematic equations of a multiple degree of freedom manipulator whose end effector is under observation. The mapping developed include forward and inverse translations from binocular images to 3-D target position and the inverse kinematics of mapping point positions into manipulator commands in joint space. Implementation is detailed for a three degree of freedom manipulator with one revolute joint at the base and two prismatic joints on the arms. The example is restricted to operate within a unit cube with arm links of 0.6 and 0.4 units respectively. The development is presented in the context of more complex simulations and a logical path for extension of the benchmark to higher degree of freedom manipulators is presented.
Collision free robot manipulator maneuvers for transferring a payload from one location to another in the presence of obstacles are discussed. Such maneuvers are executed by means of two algorithms running in parallel. The first algorithm performs an on-line, one step ahead acceleration optimization, with an adaptive N-step ahead precaution measure to prevent overshooting the specified forbidden joint coordinates. The second algorithm, an on-line planning algorithm, at the same time, selects the current target state and the current forbidden joint coordinates for the first algorithm. Since the task is a point to point transfer movement, the problem is dealt in robot joint space directly and the kinematic problem can be bypassed completely. A simulation example using a 2 degree-of-freedom planner robot is given.
The Basic Operational Robotics Instructional System (BORIS) is a six-degree-of-freedom rotational robotic manipulator system simulation used for training of fundamental robotics concepts, with in-line shoulder, offset elbow, and offset wrist. BORIS is used to provide generic robotics training to aerospace professionals including flight crews, flight controllers, and robotics instructors. It uses forward kinematic and inverse kinematic algorithms to simulate joint and end-effector motion, combined with a multibody dynamics model, moving-object contact model, and X-Windows based graphical user interfaces, coordinated in the Trick Simulation modeling environment. The motivation for development of BORIS was the need for a generic system for basic robotics training. Before BORIS, introductory robotics training was done with either the SRMS (Shuttle Remote Manipulator System) or SSRMS (Space Station Remote Manipulator System) simulations. The unique construction of each of these systems required some specialized training that distracted students from the ideas and goals of the basic robotics instruction.
Existing Proportional-Integral-Derivative (PID) robotic controllers rely on an inverse kinematic model to convert user-specified cartesian trajectory coordinates to joint variables. These joints experience friction, stiction, and gear backlash effects. Due to lack of proper linearization of these effects, modern control theory based on state space methods cannot provide adequate control for robotic systems. In the presence of loads, the dynamic behavior of robotic systems is complex and nonlinear, especially where mathematical modeling is evaluated for real-time operators. Fuzzy Logic Control is a fast emerging alternative to conventional control systems in situations where it may not be feasible to formulate an analytical model of the complex system. Fuzzy logic techniques track a user-defined trajectory without having the host computer to explicitly solve the nonlinear inverse kinematic equations. The goal is to provide a rule-based approach, which is closer to human reasoning. The approach used expresses end-point error, location of manipulator joints, and proximity to obstacles as fuzzy variables. The resulting decisions are based upon linguistic and non-numerical information. This paper presents a solution to the conventional robot controller which is independent of computationally intensive kinematic equations. Computer simulation results of this approach as obtained from software implementation are also discussed.
Telepresence is an approach to teleoperation that provides egocentric, intuitive interactions between an operator and a remote environment. This approach takes advantage of the natural cognitive and sensory motor skills of an on-board crew and effectively transfers them to a slave robot. A dual alarm dexterous robot operating under telepresence control has been developed and initial evaluations of the system performing candidate EVA, IVA and planetary geological tasks were conducted. The results of our evaluation showed that telepresence control is very effective in transferring the operator's skills to the slave robot. However, the results also showed that, due to the kinematic and dynamics inconsistencies between the operator and the robot, a limited amount of intelligent automation is also required to carry out some to the tasks. Therefore, several enhancements have been made to the original system to increase the automated capabilities of the control system without losing the benefits of telepresence.
The main objective is to introduce techniques in the areas of testing and calibration, design, and control of robotic systems. A statistical technique is described that analyzes a robot's performance and provides quantitative three-dimensional evaluation of its repeatability, accuracy, and linearity. Based on this analysis, a corrective action should be taken to compensate for any existing errors and enhance the robot's overall accuracy and performance. A comparison between robotics simulation software packages that were commercially available (SILMA, IGRIP) and that of Kennedy Space Center (ROBSIM) is also included. These computer codes simulate the kinematics and dynamics patterns of various robot arm geometries to help the design engineer in sizing and building the robot manipulator and control system. A brief discussion on an adaptive control algorithm is provided.
In advanced robot control problems, on-line computation of inverse Jacobian solution is frequently required. Parallel processing architecture is an effective way to reduce computation time. A parallel processing architecture is developed for the inverse Jacobian (inverse differential kinematic equation) of the PUMA arm. The proposed pipeline/parallel algorithm can be inplemented on an IC chip using systolic linear arrays. This implementation requires 27 processing cells and 25 time units. Computation time is thus significantly reduced.
The objective of robot calibration is to identify all parameters in a robot model so that the model represents the true robot. Each model has its own set of parameters. The authors prove that regardless of the kinematic model chosen, there are a maximum number of parameters that must be determined, implying that model accuracy cannot be improved by adding parameters. In addition, the authors demonstrate how to model any manipulator so that a minimum size Jacobian is used, thus reducing the computation required for calibration.
The primate order of animals is investigated for clues in the design of Humanoid Robots. The pursuit is directed with a theory that kinematics, musculature, perception, and cognition can be optimized for specific tasks by varying the proportions of limbs, and in particular, the points of branching in kinematic trees such as the primate skeleton. Called the Bifurcated Chain Hypothesis, the theory is that the branching proportions found in humans may be superior to other animals and primates for the tasks of dexterous manipulation and other human specialties. The primate taxa are defined, contemporary primate evolution hypotheses are critiqued, and variations within the order are noted. The kinematic branching points of the torso, limbs and fingers are studied for differences in proportions across the order, and associated with family and genus capabilities and behaviors. The human configuration of a long waist, long neck, and short arms is graded using a kinematic workspace analysis and a set of design axioms for mobile manipulation robots. It scores well. The re emergence of the human waist, seen in early Prosimians and Monkeys for arboreal balance, but lost in the terrestrial Pongidae, is postulated as benefiting human dexterity. The human combination of an articulated waist and neck will be shown to enable the use of smaller arms, achieving greater regions of workspace dexterity than the larger limbs of Gorillas and other Hominoidea.
Universal Real-Time Robotic Controller and Simulator (URRCS) is highly parallel computing architecture for control and simulation of robot motion. Result of extensive algorithmic study of different kinematic and dynamic computational problems arising in control and simulation of robot motion. Study led to development of class of efficient parallel algorithms for these problems. Represents algorithmically specialized architecture, in sense capable of exploiting common properties of this class of parallel algorithms. System with both MIMD and SIMD capabilities. Regarded as processor attached to bus of external host processor, as part of bus memory.
Incorporating multiple robotic manipulators into large-scale manufacturing systems enhances production efficiency and expands manufacturing capabilities beyond those of single-robot systems. Workpiece positioners in robotic manufacturing have demonstrated significant benefits for process optimization, but coordination strategies for multi-robot systems with shared positioners have received limited attention. This work presents a task-space coordinated trajectory-tracking control framework for multi-robot manufacturing systems, in which robots coordinate their motions within a shared, dynamic workpiece positioning frame. A workpiece positioner actively adjusts the pose of the manufactured component to enable greater operational concurrency and improve overall production efficiency. The proposed motion-coordination scheme employs a distributed and scalable architecture, supporting coordination across heterogeneous multi-robot systems. Two optimization methodologies are introduced to manage kinematic redundancies and maintain continuous, near-optimal operation throughout the manufacturing process. The first strategy exploits a task-space dimensionality reduction to achieve locally optimal configurations by leveraging symmetry-axis rotations of the tool. The second strategy utilizes the workpiece positioner to drive the coordinated robots toward stable and kinematically favorable configurations. For both optimization strategies, multiple objectives are defined to improve key performance metrics, including manipulability, configuration consistency, proximity to mechanical limits, and motion efficiency. Addressing a key limitation of existing coordination approaches, the framework is designed around online setpoint modification, allowing coordinated robots to respond effectively to in-situ process feedback. The proposed control framework is validated using the Robot Operating System (ROS) middleware on a combination of physical and simulated multi-robot system hardware.
SKITTER (Spacial Kinematic Inertial Translatory Tripod Extremity Robot) is a three-legged transport vehicle designed to perform under the unique environment of the moon. The objective of this project was to design a mechanical interface for SKITTER. This mechanical latching interface will allow SKITTER to use a series of implements such as drills, cranes, etc., and perform different tasks on the moon. The design emphasized versatility and detachability; that is, the interface design is the same for all implements, and connection and detachment is simple. After consideration of many alternatives, a system of three identical latches at each of the three interface points was chosen. The latching mechanism satisfies the design constraints because it facilitates connection and detachment. Also, the moving parts are protected from the dusty environment by housing plates.
A self contained, mobile drilling and coring system was designed to operate on the Lunar surface and be controlled remotely from earth. The system uses SKITTER (Spatial Kinematic Inertial Translatory Tripod Extremity Robot) as its foundation and produces Lunar core samples two meters long and fifty millimeters in diameter. The drill bit used for this is composed of 30 per carat diamonds in a sintered tungsten carbide matrix. To drill up to 50 m depths, the bit assembly will be attached to a drill string made from 2 m rods which will be carried in racks on SKITTER. Rotary power for drilling will be supplied by a Curvo-Synchronous motor. SKITTER is to support this system through a hexagonal shaped structure which will contain the drill motor and the power supply. A micro-coring drill will be used to remove a preliminary sample 5 mm in diameter and 20 mm long from the side of the core. This whole system is to be controlled from earth. This is carried out by a continuously monitoring PLC onboard the drill rig. A touch screen control console allows the operator on earth to monitor the progress of the operation and intervene if necessary.
Space and mass are at a premium on any space mission, and thus any machinery designed for space use should be lightweight and compact, without sacrificing strength. It is for this reason that NASA/LeRC contracted Unique Mobility Corporation to exploit their novel actuator designs to build a robot that would advance the present state of technology with respect to these requirements. Custom-designed motors are the key feature of this robot. They are compact, high-performance dc brushless servo motors with a high pole count and low inductance, thus permitting high torque generation and rapid phase commutation. Using a custom-designed digital signal processor-based controller board, the pulse width modulation power amplifiers regulate the fast dynamics of the motor currents. In addition, the programmable digital signal processor (DSP) controller permits implementation of nonlinear compensation algorithms to account for motoring vs. regeneration, torque ripple, and back-EMF. As a result, the motors produce a high torque relative to their size and weight, and can do so with good torque regulation and acceptably high velocity saturation limits. This paper presents the Unique Mobility Corporation robot prototype: its actuators, its kinematic design, its control system, and its experimental characterization. Performance results, including saturation torques, saturation velocities and tracking accuracy tests are included.
Goal Directed Model Inversion (GDMI) is an algorithm designed to generalize supervised learning to the case where target outputs are not available to the learning system. The output of the learning system becomes the input to some external device or transformation, and only the output of this device or transformation can be compared to a desired target. The fundamental driving mechanism of GDMI is to learn from success. Given that a wrong outcome is achieved, one notes that the action that produced that outcome 0 "would have been right if the outcome had been the desired one." The algorithm then proceeds as follows: (1) store the action that produced the wrong outcome as a "target" (2) redefine the wrong outcome as a desired goal (3) submit the new desired goal to the system (4) compare the new action with the target action and modify the system by using a suitable algorithm for credit assignment (Back propagation in our example) (5) resubmit the original goal. Prior publications by our group in this area focused on demonstrating empirical results based on the inverse kinematic problem for a simulated robotic arm. In this paper we apply the inversion process to much simpler analytic functions in order to elucidate the dynamic behavior of the system and to determine the sensitivity of the learning process to various parameters. This understanding will be necessary for the acceptance of GDMI as a practical tool.