2014
DOI: 10.5772/58478
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Real-Time Obstacle Avoidance for a Swarm of Autonomous Mobile Robots

Abstract: In this paper, we propose a computational trajectory generation algorithm for swarm mobile robots using local information in a dynamic environment. The algorithm plans a reference path based on constrained convex nonlinear optimization which avoids both static and dynamic obstacles. This algorithm is combined with one-step-ahead predictive control for a swarm of mobile robots to track the generated paths and reach the goals without collision. The numerical simulations and experimental results demonstrate the e… Show more

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Cited by 23 publications
(14 citation statements)
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References 26 publications
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“…A regulating agency imposes penalties when either the density of resources biomass or harvesting effort deviates from its goal. is approach of specifying a target is widely used in other areas such as engineering (see, for example, Udwadia [9] and the references therein, Çimen and Banks [10], Tan et al [11], and Hedjar and Bounkhel [12]) and production planning (see Hedjar et al [13], Hedjar et al [14], Tadj et al [15], and Bounkhel et al [16]).…”
Section: Discussionmentioning
confidence: 99%
“…A regulating agency imposes penalties when either the density of resources biomass or harvesting effort deviates from its goal. is approach of specifying a target is widely used in other areas such as engineering (see, for example, Udwadia [9] and the references therein, Çimen and Banks [10], Tan et al [11], and Hedjar and Bounkhel [12]) and production planning (see Hedjar et al [13], Hedjar et al [14], Tadj et al [15], and Bounkhel et al [16]).…”
Section: Discussionmentioning
confidence: 99%
“…If t < t 1 , we get x 2 (t) − x 1 (t) > 2R = 6, and it follows from (2) that η(t) = 0. At t = t 1 the motionx(t) hits the state constraint set C in (4.50), and hence it is reflected by a nonzero measure γ in (5). Now subtracting (4.56) from (4.57) with t = t 1 and taking into account that t1 0 η(τ )dτ = 0 tell us that 12 + t 1 (2ū 2 − 8ū 1 ) = 6, and so − 8ū 1 + 2ū 2 + 1 ≤ 0 by t 1 ≤ 6.…”
Section: Controlled Model Of Pedestrian Traffic Flowsmentioning
confidence: 99%
“…On the other hand, existence and uniqueness results for sweeping trajectories provide a convenient framework for handling simulation and related issues in various applications to mechanics, hysteresis, economics, robotics, electronics, etc. ; see, e.g., [3,4,5,6,7] among more recent publications with the references therein.To the best of our knowledge, first control problems associated with sweeping processes and first topics to investigate were related to the existence and relaxation of optimal solutions to sweeping differential…”
mentioning
confidence: 99%
“…Significance has been attributed to potential field approach, 15,16 the vector field histogram, the curvature method, and the dynamic window approach. 13 Approaches called A* 17 and D* 18 can also be considered suitable path planning methods.…”
Section: Introductionmentioning
confidence: 99%
“…8,9 Recently, many researchers have dealt with the design of control laws for obstacle avoidance and path planning of wheeled (as well as other locomotion systems) mobile robots. 4 Many different methods have been proposed in the literature by Siegwart and Nourbakhsh, 1 Zheng et al, 4 Zavlangas and Tzafestas., 12 Thrun, 11 Hedjar and Bounkhel, 13 Shi et al, 14 and their colleagues, dealing with obstacle avoidance for mobile robotics during last years. The well-known methods among them are the so-called reactive approaches, which have been proposed mainly for a single mobile robot path generation and which are suitable for real-time navigation in unknown environments.…”
Section: Introductionmentioning
confidence: 99%