This paper proposes an optimal control method to generate a minimum-torque change trajectory of humanoid arm by using a differential dynamic programming (DDP). Since DDP is a locally optimal feedback controller, the convergence is not guaranteed unless DDP starts with a good reference trajectory for high-dimensional nonlinear dynamical systems. The reference trajectory is generated by using the minimum-jerk trajectory method, and then the corresponding torque profile is obtained by using the computed-torque method. This reference trajectory is not optimal because it is solely based on the kinematics of the system. In the proposed method, the rate of torque change is used as control input in DDP to generate the optimal trajectory, which concurrently minimizes the torque variations and considers the dynamics of the system. The effectiveness of the proposed method is verified by computer simulations for generating the optimal trajectory of a 7 degrees-of-freedom (DOF) MyBot humanoid arm in Webots simulator.

This paper proposes a method to generate an optimal trajectory of nonlinear dynamical system and concurrently optimize multiple performance criteria. As the dimensionality of system increases, it is difficult to find values of cost/reward function of conventional optimal controllers. In order to solve this problem, the proposed method employs iterative linear quadratic regulator and multi-objective quantum-inspired evolutionary algorithm to generate various optimal trajectories that satisfy multiple performance criteria. Fuzzy measure and fuzzy integral are also employed for global evaluation by integrating the partial evaluation of each solution over criteria with respect to user's degree of consideration for each criterion. Effectiveness of the proposed method is verified by computer simulation carried out for the problem of stabilizing two-link inverted pendulum model.

In order to handle complex navigational commands, this paper proposes a novel algorithm that can modify a walking period and a step length in both sagittal and lateral planes. By allowing a variation of zero moment point (ZMP) over the convex hull of foot polygon, it is possible to change the center of mass (CM) position and velocity independently throughout the single support phase. This permits a range of dynamic walking motion, which is not achievable using the 3-D linear inverted pendulum mode (3D-LIPM). In addition, the proposed algorithm enables to determine the dynamic feasibility of desired motion via the construction of feasible region, which is explicitly computed from the current CM state with simple ZMP functions. Moreover, adopting the closed-form functions makes it possible to calculate the algorithm in real time. The effectiveness of the proposed algorithm is demonstrated through both computer simulation and experiment on the humanoid robot, HanSaRam-VII, developed at the Robot Intelligence Technology (RIT) laboratory, Korea Advanced Institute of Science and Technology (KAIST).

Complex navigational commands require a walk ing pattern generator that is able to modify the pattern at any point in the walking gait. This paper utilizes the 3D-LIPM(Linear Inverted Pendulum Model) for generating a walking pattern, but introduces a method that allows for manipulation of the ZMP over the convex hull of the foot polygon whilst in single support phase. This permits a range of dynamic walking states that are not achievable using the conventional 3D-LIPM. These walking states are defined as a feasible region. A real-time algorithm is then developed, which follows the cue from a complex navigational command exactly when the desired walking state is in the feasible region and chooses the nearest feasible motion when it lies outside the feasible region. The proposed scheme is both simulated and implemented on the humanoid robot HanSaRam-VII developed at RIT laboratory, KAIST.

This paper presents the development of generating dance performances of humanoid robot, HSR (HanSaRam)-VII, synchronized with Robonova, for entertainment. This heterogeneous team, RoboBees, participated in 'Robots at Play Award 2006' and nominated as one of top six teams in the world. A method of generating and combining both periodic motion (on-line pattern generator) and aperiodic motion (off-line pattern generator) is investigated along with the control architecture for HSR-VII. Detailed system descriptions of two types of humanoid robots, HSR-VII from KAIST and Robonova from miniROBOT Corp., are included with the experimental results. In addition, the time domain passivity compliance control system is introduced to guarantee the stable periodic motion by changing the initial planned trajectories. Video clip of RoboBees' performance is available at http://rit.kaist.ac.kr.

This paper proposes a control method to absorb the landing force or the ground reaction force for a stable dynamic walking of a humanoid robot. Humanoid robot may become unstable during walking due to the impulsive contact force of the sudden landing of its foot. Therefore, a control method to decrease the landing force is required. In this paper, time-domain passivity control approach is applied for this purpose. Ground and the foot of the robot are modeled as two one-port network systems that are connected, and exchange energy with each other. The time-domain passivity controller with admittance causality is implemented, which has the landing force as input and foot's position to trim off the force as output. The proposed landing force controller can enhance the stability of the walking robot from simple computation. The small-sized humanoid robot, HanSaRam-VII that has 27 DOFs, is developed to verify the proposed scheme through dynamic walking experiments.

In this paper, a method to reduce the landing impact force is proposed for a stable dynamic walking of a humanoid robot. To measure the meaningful landing impact force, a novel foot mechanism, which uses FSRs (force sensing resistors), is introduced as well. Humanoid robot might become unstable during the walking due to the impulsive contact force from the sudden landing of its foot. Therefore a new control method to decrease the landing impact force has been required. In this paper, time domain passivity control approach is applied for this purpose. Ground and the foot of the robot are modeled as two one-port network systems which are connected and exchanging energy each other. And, the time domain passivity controller which has the landing impact force as input and foot's position to trim off the force as output, is implemented. Unlike previous works, the proposed controller can guarantee the stability of the robot system without any dynamic model information at all. The small sized humanoid robot, HanSaRam-VI which has 25 DOFs, with the proposed foot mechanism is developed to verify the proposed approach through dynamic walking experiments

For the purpose of a humanoid robot's stable walking or running, it is important to absorb landing force or ground reaction force which is generated when the robot's foot lands on the ground surface. The force can make the robot unstable, and the problem becomes serious if the robot runs. This paper proposes a control system, which can absorb the landing force of a humanoid robot. Time-domain passivity control approach is applied for this purpose. Ground and the robot's foot are modeled as two one-port network systems, which are connected and exchange energy with each other. The time-domain passivity controller has the landing force as input and controls the foot's position to reduce the force. The proposed controller can guarantee the stability of the robot system without need of any dynamic model information or control parameters. Using small sized humanoid robot, dynamic walking experiments are performed to verify the proposed scheme, and its efficiency is shown from the comparison with the other scheme.