A survey of energy-efficient motion planning for wheeled mobile robots

Abstract

<jats:sec> <jats:title content-type="abstract-subheading">Purpose</jats:title> <jats:p>As wheeled mobile robots find increasing use in outdoor applications, it becomes more important to reduce energy consumption to perform more missions efficiently with limit energy supply. The purpose of this paper is to survey the current state-of-the-art on energy-efficient motion planning (EEMP) for wheeled mobile robots.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Design/methodology/approach</jats:title> <jats:p>The use of wheeled mobile robots has been increased to replace humans in performing risky missions in outdoor applications, and the requirement of motion planning with efficient energy consumption is necessary. This study analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present. The dynamic constraints play a key role in EEMP problem, which derive the power model related to energy consumption. The surveyed approaches differ in the used steering mechanisms for wheeled mobile robots, in assumptions on the structure of the environment and in computational requirements. The comparison among different EEMP methods is proposed in optimal, computation time and completeness.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Findings</jats:title> <jats:p>According to lots of literature in EEMP problem, the research results can be roughly divided into online real-time optimization and offline optimization. The energy consumption is considered during online real-time optimization, which is computationally expensive and time-consuming. The energy consumption model is used to evaluate the candidate motions offline and to obtain the optimal energy consumption motion. Sometimes, this optimization method may cause local minimal problem and even fail to track. Therefore, integrating the energy consumption model into the online motion planning will be the research trend of EEMP problem, and more comprehensive approach to EEMP problem is presented.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Research limitations/implications</jats:title> <jats:p>EEMP is closely related to robot’s dynamic constraints. This paper mainly surveyed in EEMP problem for differential steered, Ackermann-steered, skid-steered and omni-directional steered robots. Other steering mechanisms of wheeled mobile robots are not discussed in this study.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Practical implications</jats:title> <jats:p>The survey of performance of various EEMP serves as a reference for robots with different steering mechanisms using in special scenarios.</jats:p> </jats:sec> <jats:sec> <jats:title content-type="abstract-subheading">Originality/value</jats:title> <jats:p>This paper analyses a lot of motion planning technologies in terms of energy efficiency for wheeled mobile robots from 2000 to present.</jats:p> </jats:sec>

Path Planning for Autonomous Mobile Robots: A Review

“…In other words, they determine the locomotion configuration of the robot. Zhang et al [ 20 ] summarize some kinematic and dynamic models of different well-known configurations: Differential drive [ 32 ] (see Koguma robot [ 33 ] in Figure 3 a as an example and the depiction of the model in Figure 4 a), Ackermann steering [ 34 ] (see Figure 4 b,d), Skid steering [ 35 ] (see Figure 4 c) and Omnidirectional [ 36 ]. Some of them entail constraints relevant to path planning, such as the minimum turning radius of robots with Front Ackermann steering [ 37 ] (see Figure 4 b) or the high energy consumption of Skid-steering robots in turning manoeuvres [ 38 ].…”

On designing cyber-physical-social systems with energy-neutrality and real-time capabilities

“…Although the approach is energy-efficient, the main limitations are computation time, dynamic obstacles avoidance, and energy model of the robot. In [13], the paper analyses the significance of the energy cost models for different steering mechanisms and environmental model. It also shows comparative results of optimality, completeness, and computational time for different energy-efficient motion planning methods.…”

“…1) The motion unit which relies on the motors and motor drivers. Usually, the actuator of a mobile robot is a DC motor [13], but cobots can use either AC or DC motors. The cobot considered in this work is a differential drive actuated by brushless AC motors.…”

Vehicle direct yaw moment control system based on the improved linear quadratic regulator

“…Therefore, to improve the real-time performance of the system, the fuzzy control query table was established, and the values of discrete μ and two weight coefficients were forced by discrete calculation. In addition, the fuzzy control rules are processed in real number (Zhang et al , 2020), as this can avoid solving the Riccati equation online.…”