Zhiguo Lu

Transition motion from ladder climbing to brachiation for multi-locomotion robot

This paper describes a transition motion from ladder climbing to brachiation for the multi-locomotion robot (MLR). Though the transition motion is as complicated as human doing, the robot shoulder degrees of freedom (only 2 DOFs) are less than human. The paper presents how to make the robot complete complicated motion with limited freedoms. In order to prevent the motors overload, a soft adaption control which can change its style automatically according to the contact situation is used in the turning waist motion for error adjustment. Experimental results show that the MLR realize the transition motion from ladder climbing to brachiation stably and smoothly.

Motion Transfer Control From Walking to Brachiation Through Vertical Ladder Climbing for a Multi-Locomotion Robot

This paper describes a motion control approach to transfer locomotion types of a multi-locomotion robot (MLR) from walking to brachiation for maneuver performance. Brachiation is a form of arboreal locomotion in which a primate swings its body like a pendulum to transfer from a tree limb to another using its arms. In addition to multiple types of locomotion, such as biped walking, quadruped walking, and climbing a vertical ladder, the MLR performs brachiation on the horizontal ladder. The vertical ladder is used as a tool for the MLR to approach a horizontal ladder from walking on a floor. Two transition motions to transfer from waking to climbing and from climbing to brachiation are designed based on the changed environmental boundaries. In addition, a motion transfer control algorithm with grasp failure recovery is proposed by considering the reaction force and torques of robot joints. Parameters about the body positions and joint torques in the motion transfer control algorithm are set to tolerate relative position errors between the robot and its environments such as the rungs of the ladder. The proposed control method for the designed motions with error correction is experimentally verified.

Locomotion selection of Multi-Locomotion Robot based on Falling Risk and moving efficiency

This paper deals with a method of locomotion selection based on Falling Risk and moving efficiency. The robot estimates information from sensors by solving state equation. The robot evaluates the Falling Risk as an indicator of uncertainty. Falling Risk is derived from measured information by using Bayesian Network. Locomotion selection during walking is modeled as a Semi-Markov Decision Process and the most appropriate locomotion is selected by using the greedy algorithm. As a result, the robot can move in the environment that is difficult to travel by single locomotion mode, maintaining the maximum moving efficiency.

Shaping energetically efficient brachiation motion for a 24-DOF gorilla robot

We consider a 24-degrees-of-freedom monkey robot that is supposed to perform brachiation locomotion, i.e. swinging from one row of a horizontal ladder to the next one using the arms. The robot hand is constructed as a planar hook so that the contact point about which the robot swings is a passive hinge. We identify the 10 most relevant degrees of freedom for this underactuated mechanical system and formulate a tractable search: (a) introduce a family of coordination patterns to be enforced on the dynamics with respect to a path coordinate; (b) formulate geometric equality constraints that are necessary for periodic locomotion; (c) generate trajectories from integrable reduced dynamics associated with the passive hinge; (d) evaluate the energetic cost of transport. Moreover, we observe that a linear approximation of the reduced dynamics can be used for trajectory generation which allows us to incorporate the gradient of the cost function into the search algorithm.

Optimal control of energetically efficient ladder decent motion with internal stress adjustment using key joint method

For multi-contact robot motion, a closed chain is formed by robot links and the environment. This paper proposes a new methodology named “key joint method” for reducing the energy cost by adjusting an internal stress inside a closed chain. Firstly, we analyze the internal stress theoretically taking the degrees of freedom (DOF) and the number of position actuated joints into consideration, then a practical key joint method is proposed by changing a suitable redundant position controlled joint to be force control. After that, a parametric family is introduced for representing various of possible motions subjected to the robot dynamics and other constraints. Finally, a general optimization method is proposed for planning an energetically efficient multi-contact robot motion taking the motion trajectories and internal stress into consideration. As an example, the pace gait ladder decent motion is taken to explain the principle and realization of the proposed method. As experimental evaluation shows, the key joint method is effective for reducing the energy cost in the multi-contact motion.

Climbing up motion of the multi-locomotion robot (MLR) on vertical ladder with different gaits

Ladders are one of the oldest and most common tools used by human to reach a higher point. This paper describes climbing up motions on vertical ladder for a multi-locomotion robot (MLR). As potential applications, the robot with ladder climbing is expected to go to humanly inaccessible areas, taking risks to conduct searching and rescue operations instead of human. Two kinds of climbing up gaits are proposed. The posture of torso is maintained using at least three limbs in a transverse gait. The robot moves up the two limbs on the same side together in a pace gait. As a result, the travelling speed in this pace gait is higher than that in the transverse gait. The control algorithm with body motion control and error recovery is experimentally verified using the MLR which has been developed to achieve various forms of locomotion including biped walking, quadruped walking and brachiation.

Walk-to-brachiate transfer of multi-locomotion robot with error recovery

This paper describes walk-to-brachiate transfer of a multi-locomotion robot (MLR). The MLR has multiple types of locomotion such as biped walking, quadruped walking and brachiation. This transfer is carried out through vertical ladder climbing as the robot must raise its body to start brachiating. As a result we have designed two stable transfer motions from walk to climb and from climb to brachiate, while contact situations and constraints of the robot are changing during the transfers. In addition, we have proposed a control algorithm by considering the reaction force from environment, and the setting of parameter is based on a kinetic model of the robot in order to tolerate relative position errors between the robot and its environments such as rungs of the ladder. The robustness of the designed motions with error corrections is experimentally verified.

Vertical ladder climbing down motion with internal stress adjustment for a multi-locomotion robot

This paper describes a ladder climbing down motion for a multi-locomotion robot (MLR). Since a closed kinematic chain is formed by robot links and the ladder in the ladder climbing down motion, if there exist redundant position controlled joints, an internal stress would appear due to the position errors (in the environment or in the joint position, …). The internal stress has no contribution to equilibrate the robot load (weight and inertial force), however it produce greater torsional stress to the robot joint inside the closed chain. A control algorithm so that is proposed to adjust the internal stress. The primary contribution is in improving the working condition and minimizing the total squared torques of robot joints by reducing the additional internal stress. Since the pace gait is fast and flexible for robot climbing down the ladder, it is taken as an example to explain the proposed control method.

Energetically Efficient Ladder Descent Motion With Internal Stress and Body Motion Optimized for a Multilocomotion Robot

Energy efficiency of locomotion is a significant issue for autonomous mobile robots. This paper focuses on the pace gait ladder descent motion that has a closed kinematic chain formed by the robot links and the environment. To reduce the energy cost in the closed kinematic chain, we propose an optimal control strategy by optimizing the internal stress and motion trajectories in parametric form. As the main contributions of this paper, three types of energetically efficient ladder descent motions are generated with different motion-mode assumptions. Critical factors, including cycle time, horizontal distance between the robot and the vertical ladder, and value of internal stress, are analyzed theoretically. Simulation and experimental results indicate that the proposed control strategy is effective for planning an energetically efficient ladder descent motion.

Locomotion Transition Scheme of Multi-Locomotion Robot

There are researches aiming to give a high environmental adaptability to robots. Until now stable locomotion of robots in complex environment such as outside rough terrain or steep slope has been realized [1–7]. Locomotion in the most of researches adapted to complex environment has been realized by single type of locomotion form. On the other hand, we have proposed Multi-Locomotion Robot (MLR) that can perform several kinds of locomotion and has high mobility as shown in Fig. 1 [8]. By using MLR, we have realized independently biped and quadruped walking, brachiation, and climbing motion so far [9–15]. Next research issue of MLR is to develop a systematic transition system from one locomotion form to the other.