This paper presents a human--machine interface to control exoskeletons that utilizes electrical signals from the muscles of the operator as the main means of information transportation. These signals are recorded with electrodes attached to the skin on top of selected muscles and reflect the activation of the observed muscle. They are evaluated by a sophisticated but simplified biomechanical model of the human body to derive the desired action of the operator. A support action is computed in accordance to the desired action and is executed by the exoskeleton. The biomechanical model fuses results from different biomechanical and biomedical research groups and performs a sensible simplification considering the intended application. Some of the model parameters reflect properties of the individual human operator and his or her current body state. A calibration algorithm for these parameters is presented that relies exclusively on sensors mounted on the exoskeleton. An exoskeleton for knee joint support was designed and constructed to verify the model and to investigate the interaction between operator and machine in experiments with force support during everyday movements.

This paper presents a body model of intermediate level of detail to allow prediction of the knee torque produced by thigh muscles based on EMG signals. This torque prediction is used as input for a torque controller that adapts the level of support offered to an operator by a powered leg orthosis. The level of detail of the body model is chosen in such a way, that all parameters of the model can be calibrated for a specific operator with only a few sensors that are mounted on the exoskeleton.

In this paper an approach for control of autonomously flying robots with vertical take off and landing capabilities (VTOL) is presented. After reviewing that the motion description for different VTOL-robots is very similar, the general control scheme for VTOL-robots is presented. This scheme is based on linearisation and decoupling using inversion of the system model blocks. To compensate the model uncertainties and disturbances two additional parts are included into the controller: a reduced state observer based on a robot motion model as well as a disturbances observer and compensator for orientation control. The presented approach was applied to two different VTOL-robots: a helicopter and a quad-rotor. In real flight experiments it was verified that the presented general but simple controller provides sufficient performance for a wide range of practical applications.

This paper presents a force-based control mode for a hand exoskeleton. This device has been developed with focus on support of the rehabilitation process after hand injuries or strokes. As the device is designed for the later use on patients, which have limited hand mobility, fast undesired movements have to be averted. Safety precautions in the hardware and software design of the system must be taken to ensure this. The construction allows controlling motions of the finger joints. However, due to friction in gears and mechanical construction, it is not possible to move finger joints within the construction without help of actuators. Therefore force sensors are integrated into the construction to sense force exchanged between human and exoskeleton. These allow the human to control the movements of the hand exoskeleton, which is useful to teach new trajectories or can be used for diagnostic purposes. The force control scheme presented in this paper uses the force sensor values to generate a trajectory which is executed by a position control loop based on sliding mode control

Petri nets are commonly used for modeling of computer, communication, logistics and manufacturing systems. Powerful grid and cluster computers allow efficient distributed simulation of such models to speed up execution. Optimistic parallel simulation techniques have been developed for different Petri net classes. Different notions of time have been proposed to detect occurring causality violations. However, global guards in timed colored Petri nets restrict state transitions based on global conditions. Furthermore those nets may contain vanishing states and transition priorities. Those properties require an extended logical time scheme and an efficient monitoring mechanism to capture global conditions over time. The paper presents an appropriate logical time scheme that guarantees correct ordering of global states in a distributed timed colored Petri net simulation. A new mirrored state mechanism is proposed to verify global conditions without limiting the optimistic simulation behavior. Some Petri net examples are used to present performance values on a cluster computer.

In this paper, we present a method to calculate the intended motion of joints in the human body by analysing EMG signals. Those signals are emitted by the muscles attached to the adjoining bones during their activation. With the resulting intended motion, a leg orthosis can be controlled in realtime to support disabled people while walking or climbing stairs and help patients suffering from the effects of a stroke in their rehabilitation efforts. To allow a variety of different motions, a human body model with physical properties is developed and synchronized with data recorded from the pose sensors. Computing the intended motion is performed by converting calibrated EMG signals to muscle forces which animate the model. The algorithm was evaluated with experiments showing the calculated intended motion while climbing one step of a stair. The algorithm and the experimental results are both shown.

In the paper an approach for motion control of a wide class of robotic systems is presented. In this approach, the advantages of the sliding mode control (SMC) like robustness and simplicity of the control law are used. At the same time, the main disadvantage of the SMC - chattering - is avoided or at least reduced. It is shown that this approach is applicable to a wide class of robots. For this class of robots, the stability of the closed loop system is proven. The performance of the presented approach is demonstrated in a real experiment with a two arm 2/spl times/7 DoF humanoid manipulator.

Hand injuries are a frequent problem. The great amount of hand injuries is not only a problem for the affected people but economic consequences follow because rehabilitation takes a long time. Physical therapy after an operation is associated with high personnel expenses. To improve therapy results and reduce cost of rehabilitation a hand exoskeleton was developed. The hand exoskeleton was specifically designed to accomplish requirements of medical applications. For research on control algorithms and rehabilitation programs a prototype supporting all four degrees of freedom of one finger was build. The device can be easily attached and also be adjusted to deformed and scarred hands. In view of the fact that a lot of hand injuries affect only one finger, this prototype could already be functional in physical therapy. This paper presents the construction and the control system of the hand exoskeleton and possible applications in therapy of hand injuries. For the position control a PID controller was implemented and evaluated. The resulting control system allows following of recorded trajectories with sufficient accuracy.

In this paper we present a method to calibrate the surface EMG signal-to-force-relationship online. For this, a simple biomechanical model composed of bones and muscles is used. The calibration is based on an online optimization algorithm where the error between the movement of the human and the movement computed with the biomechanical model is minimized. The proposed method is part of a control system for an exoskeleton robot that should aid the wearer in everyday-life situations like walking, standing up and sitting down. In contrast to existing methods for the calculation of the EMG signal-to-force-relationship, we are not interested in the exact force values of every single muscle, but our model groups some muscles together and uses the EMG signal of one of those muscles as a representative for the group to simplify calculations. The performance of the presented method was investigated on the leg movement in sagittal plane without contact to the environment.

The mathematical description of the kinematics and dynamics of a model helicopter is presented. Using the derived closed form solution for simplified dynamics, a controller for an autonomous model helicopter is designed. This controller is composed of two loops: the inner loop for controlling the orientation of the main rotor plain and the outer loop to control the mission parameters like coordinates of some reference point, orientation or cruise velocity. The performance of the proposed controller is demonstrated for the case of position control in a computer simulation.

The presented algorithm enables a biped to perform a stable movement to a defined goal without using any precomputed trajectories. The algorithm merges the trajectory generation and the control along it, and can be used for global control, for local control along an existing trajectory, as well as for online computation of trajectories for stable movement. The algorithm is based on a decoupling of the non-linear model and changing the steering torques to account for both the overall stability of the biped and for achieving the goal. The algorithm is applied to the model of a biped moving in a sagittal plane. By specifying the goal as an arbitrary pelvis position the biped can perform movements such as sitting down or standing up. The performance of the algorithm is demonstrated in a simulation.

We present a method for calculation of time optimal movements for parking of non-holonomic mobile platforms. The parking problem is considered as a specialization of the general problem of path planning for non-holonomic robots. This is formulated as a nonlinear optimal control problem and solved using advanced numerical methods. The concept of artificial potential field is used for accounting for the obstacles in the environment. This method allows us to compute the time optimal control for all possible parking configurations (parallel, diagonal, row parking). The experiments show that using this method the movements for different complex situations can be calculated in a timely fashion.

The design of real-time systems requires modeling and analysis techniques, to ensure their correct and timely operation. In many cases a realistic model should be able to cover both fixed and stochastic times. Stochastic Petri nets are a promising description technique in this field, but mixing deterministic and randomly distributed times in one model makes the analysis often impossible. This paper shows that Petri net models with an underlying discrete time can be advantageous for the modeling and analysis of real-time systems. For a demonstration a simple application example is modeled and its behavior computed using the software tool TimeNET.

This paper deals with the problem of sensor guided grasping of moving objects. The nonlinear time optimal controller for the manipulators is presented. The inputs for the controller are parameters of the objects movement variables - position, velocity and acceleration - which are usually determined online by a sensor system. The time optimal refers to the grasping conditions-equivalence of the position, orientation and velocity of TCP and the object will be satisfied in the shortest possible time subject to all movement constrains of the manipulator joints like the maximal possible angle, velocity and acceleration.

In this paper we present a method for calculating optimal, collisionfree movements for nonholonomic mobile robots. This is formulated as a nonlinear optimal control problem and solved using advanced numerical methods. The concept of artifical potential fields is used for accounting for the obstacles in the environment. Apart from taking advantage of the large body of knowledge from the numerical methods community this has the virtue of facilitating a simple and general problem description. Experiments show that using this method, complex movements can be calculated in a timely fashion.

We present an approach to multicasting messages among highly mobile hosts in ad hoc networks. We suggest a new definition of a role-based multicast that suits the special needs of inter-vehicle communication: rather than by explicit identification, a multicast group is defined implicitly by location, speed, driving direction and time. As an example, we study a road accident that is reported to nearby vehicles. We focus on sparse deployment of the system which is likely to occur soon after the system is introduced to the market. In this state, the resulting ad hoc network tends to be disconnected. We tailor the proposed algorithm to overcome this problem of network fragmentation. Simulations show us the quality of the proposed protocol by measuring how many vehicles inside a multicast area are informed in time under various conditions.

Describes a method to detect the contact position and time/event for force/torque guided robots. The method is of special importance for interactively used robots, because the simple observation of the z-component of the force and its derivative is not sufficient in surgical environments. In these environments an undesired contact of a surgeon with the robot or an excessive change of the guiding force can be misinterpreted by the controller. For surgical applications it is important, that the surgeon can handle the system easily and intuitively. Consequently, in the described approach the system can be controlled by the surgeon by grasping the surgical tool (drilling machine, shaper, or saw) mounted on the manipulator and moving it as usual. In the paper, control schemes are proposed to achieve these features of a robotics system while the surgeon applies at the same time force to the TCP.