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We present a novel method for designing controllers for robots with variable impedance actuators. We take an imitation learning approach, whereby we learn impedance modulation strategies from observations of behaviour (for example, that of humans) and transfer these to a robotic plant with very different actuators and dynamics. In contrast to previous approaches where impedance characteristics are...
This paper develops full-state parametric controllers for standing balance of humanoid robots in response to impulsive and constant pushes. We also explore a hypothesis that postural feedback gains in standing balance should change with perturbation size. From an engineering point of view this is known as gain scheduling. We use an optimization approach to see if feedback gains should scale with the...
A difference between the human and robots from the viewpoint of motor control is a sampling time in everyday movements. That is, the sampling time for controlling conventional robot systems is required to become approximately 1 ms. On the other hand, the motor control based on human nervous system permits considerably large time-delay due to the transmission latency on afferent/efferent pathways of...
A simple, under-actuated robotic winch, called the “Winch-Bot,” is developed for surface inspection of a large object. The Winch-Bot, placed over an object surface, has only one actuator for tracing a free geometric path in a vertical plane. The cable length is controlled in relation to the direction of the cable so that the inspection end-effecter hanging at the tip of the cable can follow the path...
In the past, nonlinear dynamic systems have been proposed as a suitable representation for motor control. It has been shown that it is possible to learn desired complex control policies by a nonlinear transformation of an existing simpler control policy, which is based on a canonical dynamic system. The resulting control policies were termed dynamic movement primitives. The main result of this paper...
Augmented feedback plays an essential role in stroke rehabilitation therapy. When a force is applied to the arm, an augmented sensory (proprioceptive) cue is provided. The question was to find out if stroke patients can learn reach-and retrieval movements with error-enhanced augmented sensory feedback. The movements were performed over a predefined path, and when deviating of the path a force is provided,...
A novel control strategy based on passivity theory was proposed with special attention to trajectory tracking and robust control of rigid robot. In this paper, robot model was divided into nominal model and uncertainty part. Based on the backstepping approach, feedback passivity was used to design controller for the nominal model. A variable structure concentrated compensation controller was adopted...
This paper deals with a control approach dedicated to stable limit cycle generation for underactuated mechanical systems. The proposed approach is based on partial nonlinear feedback linearization and dynamic control for optimal periodic reference trajectories tracking. Simulation results and experiments show the efficiency of the proposed approach.
Kinodynamic planning algorithms have the potential to find feasible control trajectories which accomplish a task even in very nonlinear or constrained dynamical systems. Underactuation represents a particular form of a dynamic constraint, inherently present in many machines of interest (e.g., walking robots), and necessitates planning for long-term control solutions. A major limitation in motion planning...
Minimum-time path-tracking control of robotic manipulators assumes a relevant role in industrial applications where efficiency is an issue. On the other hand, minimizing the traveling time leads to an increment of the mechanical solicitations: the actuators dynamic limits can be easily exceeded. For this reasons, kinematic and/or dynamic constraints are normally taken into account when planning optimal...
In this paper a feedback linearization (FL) and extended state observer (ESO) based control law is proposed for the trajectory tracking control of a flexible joint robotic system. The FL based controller requires the transformed full state vector for its implementation. The design also requires exact knowledge of the system model making the controller performance sensitive to uncertainties. To address...
This paper proposes a smooth cooperated walking pattern design and feedback control based on tilt senor for biped humanoid robot. In this research, the smoothness and stability problem is the key work of the motion planning. We make the robot walk stably and naturally like a human using static Zero Moment Point (ZMP) theory and the inclination feedback control. Its basic idea is as follows: firstly,...
This paper addresses the issue of trajectory tracking control based on a neural network controller for industrial manipulators. A new control scheme is proposed based on neural network technology and linear feedback approach for tracking a planned trajectory. The control system is established with two parallel subsystems designed separately. One is a linear controller based on state feedback with...
The recent trend of humanoid robotics research has been deeply influenced by concepts such as distributed architectures, local control, force interaction and emergence of coordinated motions. A hypothesis is that feedback control from several sensors, such as force sensors and inertial devices, and more advanced control algorithms will be a key issue for the next developments. In this paper, we discuss...
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