When a humanoid robot moves in a dynamic environment, a simple process of planning and following a path may not guarantee competent performance for dynamic obstacle avoidance because the robot acquires limited information from the environment using a local vision sensor. Thus, it is essential to update its local map as frequently as possible to obtain more information through gaze control while walking. This paper proposes a fuzzy integral-based gaze control architecture incorporated with the modified-univector field-based navigation for humanoid robots. To determine the gaze direction, four criteria based on local map confidence, waypoint, self-localization, and obstacles, are defined along with their corresponding partial evaluation functions. Using the partial evaluation values and the degree of consideration for criteria, fuzzy integral is applied to each candidate gaze direction for global evaluation. For the effective dynamic obstacle avoidance, partial evaluation functions about self-localization error and surrounding obstacles are also used for generating virtual dynamic obstacle for the modified-univector field method which generates the path and velocity of robot toward the next waypoint. The proposed architecture is verified through the comparison with the conventional weighted sum-based approach with the simulations using a developed simulator for HanSaRam-IX (HSR-IX).

This paper proposes a novel evolutionary multiobjective footstep planner for humanoid robots. First, a footstep planner using a univector field navigation method is proposed to provide a command state (CS), which is to be an input of a modifiable walking pattern generator (MWPG) at each footstep. Then, the MWPG generates corresponding trajectories for every leg joint of the humanoid robot at each footstep to follow the CS. Second, a multiobjective evolutionary algorithm (MOEA) is employed to optimize the univector fields satisfying multiple objectives in navigation. Finally, a preference-based selection algorithm based on a fuzzy measure and fuzzy integral is proposed to select the preferred one out of various nondominated solutions obtained by the MOEA. The effectiveness of the proposed evolutionary multiobjective footstep planner is demonstrated through computer simulations for a simulation model of a small-sized humanoid robot, HanSaRam-VIII.

This paper proposes a navigation framework for humanoid robots, which integrates gaze control and modified univector field-based path planning to cope with moving obstacles. To make navigation robust, obstacles are modeled according to their relative velocities and positions. Moreover, partial evaluation values for gaze control architecture are also considered for modifying their virtual size and moving trajectory. In addition, gaze control architecture is proposed, which estimates the size of local map confidence area, self-localization error, surrounding obstacles and obstacle-free distance against those obstacles in the local map. The proposed framework is verified through computer simulations by using a developed simulator for HanSaRam-VIII.

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.

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.