A Depth Space Approach for Evaluating Distance to Objects -- with Application to Human-Robot Collision Avoidance

We present a novel approach to estimate the distance between a generic point in the Cartesian space and objects detected with a depth sensor. This information is crucial in many robotic applications, e.g., for collision avoidance, contact point identification, and augmented reality. The key idea is to perform all distance evaluations directly in the depth space. This allows distance estimation by considering also the frustum generated by the pixel on the depth image, which takes into account both the pixel size and the occluded points. Different techniques to aggregate distance data coming from multiple object points are proposed. We compare the Depth space approach with the commonly used Cartesian space or Configuration space approaches, showing that the presented method provides better results and faster execution times. An application to human-robot collision avoidance using a KUKA LWR IV robot and a Microsoft Kinect sensor illustrates the effectiveness of the approach

The explicit dynamic model and inertial parameters of the PUMA 560 arm

To provide COSMOS, a dynamic model based manipulator control system, with an improved dynamic model, a PUMA 560 arm was disassembled; the inertial properties of the individual links were measured; and an explicit model incorporating all of the non-zero measured parameters was derived. The explicit model of the PUMA arm has been obtained with a derivation procedure comprised of several heuristic rules for simplification. A simplified model, abbreviated from the full explicit model with a 1% significance criterion, can be evaluated with 805 calculations, one fifth the number required by the recursive Newton-Euler method. The procedure used to derive the model is laid out; the measured inertial parameters are presented, and the model is included in an appendix

Least action principles and their application to constrained and task-level problems in robotics and biomechanics

International audienceLeast action principles provide an insightful starting point from which problems involving constraints and task-level objectives can be addressed. In this paper, the principle of least action is first treated with regard to holonomic constraints in multibody systems. A variant of this, the principle of least curvature or straightest path, is then investigated in the context of geodesic paths on constrained motion manifolds. Subsequently, task space descriptions are addressed and the operational space approach is interpreted in terms of least action. Task-level control is then applied to the problem of cost minimization. Finally, task-level optimization is formulated with respect to extremizing an objective criterion, where the criterion is interpreted as the action of the system. Examples are presented which illustrate these approaches

Control of Redundant Robots Under Hard Joint Constraints: Saturation in the Null Space

We present an efficient method for addressing online the inversion of differential task kinematics for redundant manipulators, in the presence of hard limits on joint space motion that can never be violated. The proposed SNS (Saturation in the Null Space) algorithm proceeds by successively discarding the use of joints that would exceed their motion bounds when using the minimum norm solution. When processing multiple tasks with priority, the SNS method realizes a preemptive strategy by preserving the correct order of priority in spite of the presence of saturations. In the single- and multi-task case, the algorithm automatically integrates a least possible task scaling procedure, when an original task is found to be unfeasible. The optimality properties of the SNS algorithm are analyzed by considering an associated Quadratic Programming problem. Its solution leads to a variant of the algorithm, which guarantees optimality also when the basic SNS algorithm does not. Numerically efficient versions of these algorithms are proposed. Their performance allows real-time control of robots executing many prioritized tasks with a large number of hard bounds. Experimental results are reported

NEW TYPE OF LIGHTWEIGHT AGGREGATE FOR USE IN STRUCTURAL CONCRETE

This research studied the utilization of municipal solid waste incineration bottom ash (MSWI-BA) in lightweight coarse aggregate (LWC) production. A special method was followed to prepare the new aggregate to fully replace the normal aggregates (NWA) in concrete. The mechanical properties such as compressive strength, tensile strength, and elasticity modulus were investigated for the LWC concrete. Then, two beams were prepared; one from LWC and the other from NWC. The structural performance of beams made up of lightweight aggregates compared to normal aggregates was investigated. The results showed that this type of aggregates led to a 20% reduction in concrete density. There was a decrease in compressive strength, tensile strength, and elasticity modulus when using lightweight aggregates. In addition, there was a reduction in the structural performance of the NWC beam was better than the LWC bea

Motion and force control of robot manipulators

In this paper we present a unified approach for the control of manipulator motions and active forces based on the operational space formulation. The end-effector dynamic model is used in the development of a control system in which the generalized operational space end-effector forces are selected as the command vector. This formulation provides a framework for natural and efficient integration of both end-effector force and motion control. A "generalized position and force specification matrix" is used for the specification of tasks that involve simultaneous motion and force operations. Flexibility in the force sensor, end-effector, and environment, and problems related to impact are discussed. The real-time operational space control system, COSMOS, has been recently implemented in the NYMPH multiprocessor system. Results of experiments involving contact and force step input response are presented