Typical mobile robot structures (e.g. wheelchairs or car-like robots) do not have the required mobility for common applications such as displacement in an office, hospital, workshop, etc. New structures based on the “universal wheel” (i.e. a wheel equipped with freely rotating rollers) have been developed to increase mobility. However, these structures have important drawbacks such as spurious vibrations and limited load capacity. This paper presents a new type of omnimobile platform using an original combination of spherical wheel and universal wheel. This structure will improve the robot capabilities, i.e., load capacity and surmountable bumps.

One of the simplest and natural appealing motion control strategies for robot manipulators is the PD control with feedforward compensation. Although successful experimental tests of this control scheme have been published since the beginning of the eighties, the proof of global asymptotic stability has remained unattended until now. The contribution of this paper is to prove that global asymptotic stability can be guaranteed provided that the proportional and derivative gains are adequately selected. The performance of the PD control with feedforward compensation evaluated on a two degrees-of-freedom direct-drive arm appears as fine as the classical model-based computed torque control scheme.

This paper analyzes the dynamics and control of pinch motions generated by a pair of two multi-degrees-of-freedom robot fingers with soft and deformable tips pinching a rigid object. It is shown firstly that passivity analysis leads to an effective design of a feedback control signal that realizes dynamic stable pinching (grasping), even if extra terms of Lagrange's multipliers arise from holonomic constraints of tight area-contacts between soft finger-tips and surfaces of the rigid object and exert torques and forces on the dynamics. It is shown secondly that a principle of superposition is applicable to the design of additional feedback signals for controlling both the posture (rotational angle) and position (some of task coordinates of the mass center) of the object provided that the number of degrees of freedom of each finger is specified for satisfying a condition of stationary resolution of controlled position state variables. The details of feedback signals are presented in the case of a special setup consisting of two robot fingers with two degrees of freedom.

Near minimum-time direct voltage control (DVC) algorithms synthesizing path-planning and path-following are proposed for wheeled mobile robots (WMRs) satisfying (i) initial and final postures and velocities as well as (ii) voltage and current constraints. To overcome nonholonomic and nonlinear properties of WMRs, we divide our control algorithm for cornering motion into three sections: TSD (Translational Section of Deceleration), RS (Rotational Section), and TSA (Translational Section of Acceleration). We developed off-line DVC algorithms using the quadratic problem with the object function minimizing the total time, where voltages to the motors are controlled directly without velocity/torque-servo modules, while satisfying the current constraints. Two methods of searching for the two control parameters (number of steps for RS MR and velocity constraint in RS β) were considered: The one is composed of one simple 1-dimensional search for β, and the other is composed of two 1-dimensional searches for MR and β which has better performance. Performances of the proposed control algorithms are validated via various simulations.

The design and implementation of adaptive control for nonlinear unknown systems is extremely difficult. The nonlinear adaptive control for assembly robots performing a peg-in-hole insertion is one such an example. The recently intensively studied neural networks brings a new stage in the development of adaptive control, particularly for unknown nonlinear systems. The aim of this paper is to propose a new approach of hybrid force position control of an assembly robot based on artificial neural networks systems. An appropriate neural network is used to model the plant and is updated online. An artificial neural network controller is then directly evaluated using the updated neuro model. Two control structures are proposed and the stability analysis of the closed-loop system is investigated using the Lyapunov method. Experimental results demonstrate that the identification and control schemes suggested in this paper are efficient in practice.

We present a data fusion control scheme for the hand-held camera of the SCORBOT-ER VII robot arm for learning visual tracking and interception. The control scheme consists of two modules: The first one generates candidate actions to drive the end-effector as accurate as possible directly above a moving target, so that the second module can handily take over to intercept it. The desired camera-joint coordinate mappings are generalized by Elman neural networks for a tracking module. The intercept module then determines a suitable intercept trajectory for the robot within the required conditions. The simulation results support the claim that it could be successfully applied to track and intercept a moving target.

In this paper a method for the automatic generation of dynamics for modular robots is presented. A modular reconfigurable robot consists of link modules and joint modules of various specifications. We analyze the abstract architecture of modular robots. A total of nine types of connecting forms and three types of joint forms are identified with reference to their own systems. The geometric relationships are derived by the group theory. According to the modular idea, the formulations of the velocity, acceleration and other essential equations of the link module and the joint module are formed compensatively and recursively. Then the dynamic model is generated automatically by a compensative and recursive method.

In this paper, the kinematic workspace characteristics of a crab-like legged vehicle are investigated using a 2-D model. The alternative kinematic configurations and their corresponding workspace constraints are discussed, and the vehicle configuration of most interest identified. It is shown that, for constant vehicle body attitude, only two parameters affect the kinematic workspace, foot overlap and thigh length. Analytical methods for calculating the workspace characteristics are presented and, using these methods, the effects of the design geometry on the kinematic workspace are investigated.

This study presents a fast inverse kinematics algorithm for a class of robots, including PUMA and SCARA. It decomposes a robot Jacobian into a product of sub-matrices to locate singularities. Singular value decomposition (SVD) is applied to each singular sub-matrix to find a local least-squares inverse. Perfect inverses are derived for all non-singular sub-matrices. The proposed algorithm is extremely fast. A total inverse requires 54 flops for PUMA and 43 for SCARA. Simulation and experiment are conducted to test the accuracy and real-time speed of the algorithm.

The aim of this paper is to propose a bipedal structure able to follow high acceleration movements. The vertical jump of a human has been chosen as input (coming from experiments) to validate the controller design as it is one of the most complex motion. The study concerns the low level of the biped control that is to say the control design of one leg made of three rigid bodies, each of them moved by a pneumatic actuator. An analogy between a pneumatic actuator and a physiological muscle is first proposed. A dynamic model of the leg is then presented decoupling the dynamic effects of the skeletal (as interactions between segments) from the dynamic effects of the muscles involved. The controller is based on the nonlinear theory (taking into account the actuator and the mechanical models), it ensures a dynamic tracking of position and force. Its originality lays in the consideration of impedance behaviour at each joint during free and constrained tasks. It leads to asymptotically stable (Popov criteria) control laws which are continuous between contact and non-contact phases enabling real-time computations. The simulation results clearly show the tracking of position and forces during the whole jump cycle.

We propose an event-driven algorithm for the control of simple robot assembly problems based on noncooperative game theory. We examine rigorously the simplest setting – three bodies with one degree of freedom and offer extensive simulations for the 2 DOF extension. The initial analysis and the accompanying simulations suggest that this approach may indeed, offer an attractive means of building robust event driven assembly systems.