Recursive forward dynamics for multiple robot arms moving a common task object

Recursive forward dynamics algorithms are developed for an arbitrary number of robot arms moving a commonly held object. The multiarm forward dynamics problem is to find the angular accelerations at the joints and the contact forces that the arms impart to the task object. The problem also involves finding the acceleration of this object. The multiarm forward dynamics solutions provide a thorough physical and mathematical understanding of the way several arms behave in response to a set of applied joint moments. Such an understanding simplifies and guides the subsequent control design and experimentation process. The forward dynamics algorithms also provide the necessary analytical foundation for conducting analysis and simulation studies. The multiarm algorithms are based on the filtering and smoothing approach recently advanced for single-arm dynamics, and they can be built up modularly from the single-arm algorithms. The algorithms compute recursively the joint-angle accelerations, the contact forces, and the task-object accelerations. Algorithms are also developed to evaluate in closed form the linear transformations from the active joint moments to the joint-angle accelerations, to the task-object accelerations., and to the task-object contact forces. A possible computing architecture is presented as a precursor to a more complete investigation of the computational performance of the dynamics algorithms

Important Considerations in Force Control With Applications to Multi-Arm Manipulation

This paper addresses force control in overconstrained dynamic systems with special emphasis on robot control and multiarm coordination. Previous approaches to force control are studied and many of these are shown to be unsuitable for dynamic force control. Practical and theoretical considerations for designing force control algorithms are discussed. Experimental and simulation results that validate the theoretical findings are presented for a single-degree-of-freedom pneumatic force controller. Finally the theoretical development of a two-arm manipulation system with an extended statespace formulation and a computer simulation of the system are presented to illustrate the application of the basic ideas to a more complicated system

Information Acquisition with Sensing Robots: Algorithms and Error Bounds

Utilizing the capabilities of configurable sensing systems requires addressing difficult information gathering problems. Near-optimal approaches exist for sensing systems without internal states. However, when it comes to optimizing the trajectories of mobile sensors the solutions are often greedy and rarely provide performance guarantees. Notably, under linear Gaussian assumptions, the problem becomes deterministic and can be solved off-line. Approaches based on submodularity have been applied by ignoring the sensor dynamics and greedily selecting informative locations in the environment. This paper presents a non-greedy algorithm with suboptimality guarantees, which does not rely on submodularity and takes the sensor dynamics into account. Our method performs provably better than the widely used greedy one. Coupled with linearization and model predictive control, it can be used to generate adaptive policies for mobile sensors with non-linear sensing models. Applications in gas concentration mapping and target tracking are presented.Comment: 9 pages (two-column); 2 figures; Manuscript submitted to the 2014 IEEE International Conference on Robotics and Automatio

A Kinematic Approach to Determining the Optimal Actuator Sensor Architecture for Space Robots

Autonomous space robots will be required for such future missions as the construction of large space structures and repairing disabled satellites. These robots will need to be precisely controlled. However, factors such as manipulator joint/actuator friction and spacecraft attitude control thruster inaccuracies can substantially degrade control system performance. Sensor-based control algorithms can be used to mitigate the effects of actuator error, but sensors can add substantially to a space system’s weight, complexity, and cost, and reduce its reliability. Here, a method is presented to determine the sensor architecture that uses the minimum number of sensors that can simultaneously compensate for errors and disturbance in a space robot’s manipulator joint actuators, spacecraft thrusters, and reaction wheels. The placement and minimal number of sensors is determined by analytically structuring the system into “canonical chains” that consist of the manipulator links and spacecraft with force/torque sensors placed between the space robot’s spacecraft and its manipulators. These chains are combined to determine the number of sensors needed for the entire system. Examples of one- and two-manipulator space robots are studied and the results are validated by simulation

Orientation and Workspace Analysis of the Multifingered Metamorphic Hand-Metahand

This paper introduces for the first time a metamorphic palm and presents a novel multifingered hand, known as Matahand, with a foldable and flexible palm that makes the hand adaptable and reconfigurable. The orientation and pose of the new robotic hand are enhanced by additional motion of the palm, and workspace of the robotic fingers is complemented with the palm motion. To analyze this enhanced workspace, this paper introduces finger-orientation planes to relate the finger orientation to palm various configurations. Normals of these orientation planes are used to construct a Gauss map. Adding an additional dimension, a 4-D ruled surface is generated to illustrate orientation and pose change of the hand, and an orientation–pose manifold is developed from the orientation–pose ruled surface. The orientation and workspace analysis are further developed by introducing a triangular palm workspace that evolves into a helical surface and is further developed into a 4-D representation. Simulations are presented to illustrate the characteristics of this new dexterous hand

Hierarchical Task Planning for Multiarm Robot with Multiconstraint

Multiarm systems become the trends of space robots, for the on-orbit servicing missions are becoming more complex and various. A hierarchical task planning method with multiconstraint for multiarm space robot is presented in this paper. The process of task planning is separated into two hierarchies: mission profile analysis and task node planning. In mission profile analysis, several kinds of primitive tasks and operators are defined. Then, a complex task can be decomposed into a sequence of primitive tasks by using hierarchical task network (HTN) with those primitive tasks and operators. In task node planning, A⁎ algorithm is improved to adapt the continuous motion of manipulator. Then, some of the primitive tasks which cannot be executed directly because of constraints are further decomposed into several task nodes by using improved A⁎ algorithm. Finally, manipulators execute the task by moving from one node to another with a simple path plan algorithm. The feasibility and effectiveness of the proposed task planning method are verified by simulation

Optimal control of redundant robots in human-like fashion

U ovom radu je predložen jedan novi vid upravljanja redundantnim robotskim sistemom. To je ostvareno primenom pogodnog kinematičkog i dinamičkog kriterijuma zasnovanim na biološkim principima tj. na načinu koji je sličan i svojstven čoveku. Ovde je dinamički model robotskog sistema dat u formi Langranžeovih jednačina druge vrste u kovarijatnom obliku.Nekoliko kriterijuma je uvedeno koji su funkcija generalisanih koordinata, brzina vektora ubrzanja kao i vektora upravljanja respektivno. Konačno, efikasnost predloženog optimalnog upravljanja na način sličan čoveku je demonstrirana na robotu sa četiri stepena slobode.This paper suggests a new optimal control of a redundant robotic system. It is achieved using suitable kinematic and dynamic criteria based on biological principles, i.e. in human-like fashion. Here, a dynamical model of robotic system is given in the form of Langrange's equations of second kind in covariant form. Several criteria are introduced which are the function of generalized coordinates, velocities, accelerations and control vectors, respectively. Finally, the effectiveness of suggested optimal control in human-like fashion is demonstrated with a robot with four degrees of freedom as the illustrative example

Optimal control of redundant robots in human-like fashion

U ovom radu je predložen jedan novi vid upravljanja redundantnim robotskim sistemom. To je ostvareno primenom pogodnog kinematičkog i dinamičkog kriterijuma zasnovanim na biološkim principima tj. na načinu koji je sličan i svojstven čoveku. Ovde je dinamički model robotskog sistema dat u formi Langranžeovih jednačina druge vrste u kovarijatnom obliku.Nekoliko kriterijuma je uvedeno koji su funkcija generalisanih koordinata, brzina vektora ubrzanja kao i vektora upravljanja respektivno. Konačno, efikasnost predloženog optimalnog upravljanja na način sličan čoveku je demonstrirana na robotu sa četiri stepena slobode.This paper suggests a new optimal control of a redundant robotic system. It is achieved using suitable kinematic and dynamic criteria based on biological principles, i.e. in human-like fashion. Here, a dynamical model of robotic system is given in the form of Langrange's equations of second kind in covariant form. Several criteria are introduced which are the function of generalized coordinates, velocities, accelerations and control vectors, respectively. Finally, the effectiveness of suggested optimal control in human-like fashion is demonstrated with a robot with four degrees of freedom as the illustrative example