Optimal motion planning and control of a nonholonomic spherical robot using dynamic programming approach: simulation and experimental results

Roozegar, M.; Mahjoob, M. J.; Jahromi, M.J. Zeini

doi:10.1016/j.mechatronics.2016.05.002

Cited by 35 publications

(16 citation statements)

References 18 publications

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“…Nevertheless, energy E lost during the differential drive movement equals E = 4.81 for control scheme (42) and E = 4.1 for our iterative procedure, respectively, where E = T 0 ||v|| 2 dt. Inverse-free trajectory generator (28) has also been started with g k = 0.3 and initial control v 0 = 0 which is singular for iterative procedure (42). The convergence result for this simulation is given in Fig.…”

Section: Numerical Comparisons Of the Proposed Control Scheme With Thmentioning

confidence: 93%

“…Consequently, iterative scheme (28) seems to be more energy-saving than that given by formula (42). In the last simulation of this section, we tried to find the most energy-saving solution for the analysed positioning task.…”

Section: Numerical Comparisons Of the Proposed Control Scheme With Thmentioning

confidence: 99%

“…In such context, three representative approaches to the non-holonomic motion planning problem may be distinguished. The graph search-based methods including those offered in [13,28,29,33,42] generally involve some types of decomposition of the state space into cells (e.g. probabilistic road maps (PRM), rapidly exploring random trees (RRT) or uniform discrete grid representation).…”

Section: Introductionmentioning

confidence: 99%

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The planning of optimal motions of non-holonomic systems

Galicki

2017

Nonlinear Dyn

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A new method to the planning of optimal motions of the non-holonomic systems is presented. It is based on a non-classical formulation of the Pontryagin Maximum Principle given in variational form, which handles efficiently various control and/or statedependent constraints. They arise naturally due to both physical limits of the actuators of the non-holonomic systems and potential existence of obstacles in the workspace. The method proposed here provides continuous solutions in infinite-dimensional control space. It seems to be in contrast to majority of known optimization algorithms which project infinite-dimensional control space into finite-dimensional one and then apply techniques of linear and/or nonlinear programming, thus resulting only in near-optimal trajectories. Moreover, the offered control schemes do not require computation of inverse or pseudo-inverse of the Jacobian in the case of classic non-holonomic motion planning what also results in numerical stability of our approach. The performance of the proposed control strategies is illustrated through computer simulations for a chosen class of non-holonomic structures operating in both an obstacle-free workspace and a workspace including obstacles. Numerical comparison of our control scheme with the representative algorithms known from the literature is also given.

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Section: Numerical Comparisons Of the Proposed Control Scheme With Thmentioning

confidence: 93%

Section: Numerical Comparisons Of the Proposed Control Scheme With Thmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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The planning of optimal motions of non-holonomic systems

Galicki

2017

Nonlinear Dyn

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“…In order to achieve trajectory tracking, it is necessary to establish the kinematics and dynamics model of the Dobot manipulator. The specific feedback control process is shown in Figure 3 [15].…”

Section: B the Softwarementioning

confidence: 99%

Implementing Multi-DOF Trajectory Tracking Control System for Robotic Arm Experimental Platform

Yang²,

Li³

et al. 2018

2018 10th International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

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To implement the control system of a multi-DOF robotic manipulator (Dobot), the robot dynamics, trajectory planning algorithm and motion control strategy are studied for designing the trajectory tracking control system. In this paper, the hardware and software of Dobot magician control system are designed. The hardware mainly includes STM32 controller. The software part mainly builds the host computer display interface, completes the protocol communication between the robot manipulator and the PC, so as to realize the trajectory tracking control of the robot manipulator and implement the trackfollowing in real time. The experimental results show that the control system can accurately track the trajectory of robotic manipulator with a certain degree of real-time and stability.

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“…Nonholonomic robots [8,9], being one of the vastly developed categories, have wide applications in surveillance and transportation. Various locomotion mechanisms [10,11,12,13] have been employed depending on the application environment.…”

Section: Introductionmentioning

confidence: 99%

A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots

Fang

Vibhute

Soh

et al. 2017

Sensors

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Due to their efficient locomotion and natural tolerance to hazardous environments, spherical robots have wide applications in security surveillance, exploration of unknown territory and emergency response. Numerous studies have been conducted on the driving mechanism, motion planning and trajectory tracking methods of spherical robots, yet very limited studies have been conducted regarding the obstacle avoidance capability of spherical robots. Most of the existing spherical robots rely on the “hit and run” technique, which has been argued to be a reasonable strategy because spherical robots have an inherent ability to recover from collisions. Without protruding components, they will not become stuck and can simply roll back after running into bstacles. However, for small scale spherical robots that contain sensitive surveillance sensors and cannot afford to utilize heavy protective shells, the absence of obstacle avoidance solutions would leave the robot at the mercy of potentially dangerous obstacles. In this paper, a compact magnetic field-based obstacle detection and avoidance system has been developed for miniature spherical robots. It utilizes a passive magnetic field so that the system is both compact and power efficient. The proposed system can detect not only the presence, but also the approaching direction of a ferromagnetic obstacle, therefore, an intelligent avoidance behavior can be generated by adapting the trajectory tracking method with the detection information. Design optimization is conducted to enhance the obstacle detection performance and detailed avoidance strategies are devised. Experimental results are also presented for validation purposes.

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Optimal motion planning and control of a nonholonomic spherical robot using dynamic programming approach: simulation and experimental results

Cited by 35 publications

References 18 publications

The planning of optimal motions of non-holonomic systems

The planning of optimal motions of non-holonomic systems

Implementing Multi-DOF Trajectory Tracking Control System for Robotic Arm Experimental Platform

A Compact Magnetic Field-Based Obstacle Detection and Avoidance System for Miniature Spherical Robots

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