Energy Consumption Of Robot Research Articles

Energy-Efficiency-Based Gait Control System Architecture and Algorithm for Biped Robots

A novel systematic architecture and algorithm of gait control based on energy-efficiency optimization is represented, aiming at the fatal problem of high energy consumption for biped robots walking in unstructured environments. By designing an optimal controller to minimize the energy criterion, the proposed method provides a remarkable descend rate of energy consumption in the trunk-rotation walking mechanism. The proposed algorithm is able to optimize the trunk trajectory by minimizing the energy-related cost function while guaranteeing zero-moment point (ZMP) criterion. Simulations and experimental results show the validity of the method.

Dynamic modeling, stability and energy consumption analysis of a realistic six-legged walking robot

This paper deals with a detailed analysis on kinematics, dynamics, stability and energy consumption of a realistic six-legged robot. The aim of this study is to extend a previous work of Roy et al. [1], in order to estimate optimal feet forces and joint torques of the six-legged robot generating wave-gaits with four different duty factors and deal with its stability issues. Two different approaches are developed to determine optimal feet forces. In the first approach, minimization of the norm of feet forces is carried out using a least square method, whereas minimization of the norm of joint torques is performed in the second approach. The second approach is found to be more energy efficient compared to the first one. The maximum values of feet forces and joint torques are seen to decrease with the increase of duty factor. The effects of walking parameters, namely velocity, stroke and duty factors have been studied on energy consumption and stability of the robot. The variations of average power consumption and specific energy consumption with the velocity and stroke are compared for four different duty factors. Wave gait with a low duty factor is found to be more energy-efficient compared to that with a high duty factor at the highest possible velocity.

Design and Implementation of Service Robot Lightweight Dual-Arm Based on CAN Bus

Because high positioning accuracy of industrial robots requires high stiffness at the price of high robot mass and energy consumption relative to the payload of the robot, this paper describes a kind of service robot dual-arm constructed by lightweight reconfigurable modules. After analyzing the composition characteristics of service robot dual-arm, the type selection of robot arm modules is accomplished, and the hardware platform of robot dual-arm composed by modular joint is builded. According to the modularization characteristics of arm joints, the distributed control system is designed.

Dynamic Modeling of Energy Efficient Crab Walking of Hexapod Robot

Crab walking is the most general and very important one for omni-directional walking of a hexapod robot. This paper presents a dynamic model for determining energy consumption and energy efficiency of a hexapod robot during its locomotion over flat terrain with a constant crab angle. The model has been derived for statically stable crab-wave gaits by considering a minimization of dissipating energy for optimal foot force distribution. Two approaches, such as minimization of norm of feet forces and minimization of norm of joint torques have been developed. The variations of average power consumption and energy consumption per weight per traveled length with velocity or stroke have been compared for crab walking with tripod and tetrapod gait patterns. Tetrapod gaits are found to be more energy-efficient compared to the tripod gaits.

Soft computing-based approaches to predict energy consumption and stability margin of six-legged robots moving on gradient terrains

Soft computing-based approaches have been developed to predict specific energy consumption and stability margin of a six-legged robot ascending and descending some gradient terrains. Three different neuro-fuzzy and one neural network-based approaches have been developed. The performances of these approaches are compared among themselves, through computer simulations. Genetic algorithm-tuned multiple adaptive neuro-fuzzy inference system is found to perform better than other three approaches for predicting both the outputs. This could be due to a more exhaustive search carried out by the genetic algorithm in comparison with back-propagation algorithm and the use of two separate adaptive neuro-fuzzy inference systems for two different outputs. A designer may use the developed soft computing-based approaches in order to predict specific energy consumption and stability margin of the robot for a set of input parameters, beforehand.

Development of a compliance controller to reduce energy consumption for bipedal robots

In this paper a strategy is proposed to combine active trajectory tracking for bipedal robots with exploiting the natural dynamics by simultaneously controlling the torque and stiffness of a compliant actuator. The goal of this research is to preserve the versatility of actively controlled humanoids, while reducing their energy consumption. The biped Lucy, powered by pleated pneumatic artificial muscles, has been built and controlled and is able to walk up to a speed of 0.15 m/s. The pressures inside the muscles are controlled by a joint trajectory tracking controller to track the desired joint trajectories calculated by a trajectory generator. However, the actuators are set to a fixed stiffness value. In this paper a compliance controller is presented to reduce the energy consumption by controlling the stiffness. A mathematical formulation has been developed to find an optimal stiffness setting depending on the desired trajectory and physical properties of the system and the proposed strategy has been validated on a pendulum structure powered by artificial muscles. This strategy has not been implemented on the real robot because the walking speed of the robot is currently too slow to benefit already from compliance control.

1819 障害物環境下における4足歩行ロボットの移動エネルギーに基づく脚軌道最適化(OS18.計算力学と最適化(3),ポスターセッションP-4)

1819 障害物環境下における4足歩行ロボットの移動エネルギーに基づく脚軌道最適化(OS18.計算力学と最適化(3),ポスターセッションP-4)

Study on Identification of Dynamics of Underwater Manipulator and its Trajectory Planning Based on Minimum Energy Consumption

Recently, ROV and AUV are often used in the maintenance of the offshore structures and the development of the ocean resources. These operations are carried out with underwater manipulator of the robot. As the energy consumption of untethered type ocean robot is limited, it is required to save energy during operation. But in order to calculate the target trajectory for minimum energy consumption, precise mathematical model of the dynamics of the manipulator is required.In this paper, we try to apply the Learning Feed-Forward Controller (LFFC) to identify the dynamics of the controlled object, especially friction force acting on the joint. Using the identification results, we formulate and calculate the trajectory of the minimum energy consumption, then examine the effect of the trajectory planning method by model experiments.As a result of the study, it is shown that the dynamics of the controlled object can be identified precisely with LFFC, and that the trajectory obtained from the solution of the two point boundary value problem is nearly equal to the actual trajectory of minimum energy consumption.