Obstacle avoidance and motion planning scheme for a hexapod robot Octopus-III

Zhao, Yue; Chai, Xun; Gao, Feng; Qi, Chenkun

doi:10.1016/j.robot.2018.01.007

Cited by 68 publications

(33 citation statements)

References 18 publications

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“…Space perception is a central issue in mobile robotics. Indeed, many abilities heavily depend on it as they are deeply rooted on spatial knowledge: among others, one can cite trajectory planning [1], obstacle avoidance [2], auditory and visual sensing [3], etc. Most of these works consider that space is something that exists objectively out there, and try to exploit it to model mechanical systems, localize some objects of interest, reach and catch moving targets, etc.…”

Section: Introductionmentioning

confidence: 99%

Where Do I Move My Sensors? Emergence of a Topological Representation of Sensors Poses From the Sensorimotor Flow

Marcel

Argentieri

Gas

2021

IEEE Trans. Cogn. Dev. Syst.

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This paper deals with the perception of mobile robotic systems within the framework of interactive perception, and inspired by the sensorimotor contingencies (SMC) theory. These approaches state that perception arises from active exploration of an environment. In the SMC theory, it is postulated that information about the structure of space could be recovered from a quasi-uninterpreted sensorimotor flow. In a recent article, the authors have provided a mathematical framework for the construction of a sensorimotor representation of the interaction between the sensors and the body of a naive agent, provided that the sensory inputs come from the agent's own body. An extension of these results, with stimulations coming from an unknown changing environment, is proposed in this paper. More precisely it is demonstrated that, through repeated explorations of its motor configurations, the perceived sensory invariants can be exploited to build a topologically accurate internal representation of the relative poses of the agent's sensors in the physical world. Precise theoretical considerations are provided as well as an experimental framework. Finally, some examples that serve as proofs of concepts are analysed in both simulated and realistic environments.

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Section: Introductionmentioning

confidence: 99%

Where Do I Move My Sensors? Emergence of a Topological Representation of Sensors Poses From the Sensorimotor Flow

Marcel

Argentieri

Gas

2021

IEEE Trans. Cogn. Dev. Syst.

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“…Various requirements of obstacle avoidance can be satisfied for the changing distance between robot and the obstacles [4]. The issue of obstacle avoidance is treated as an optimization problem in [5]. On the unmarked path, dynamic colour perception model for the autonomous navigation is explained in [6].…”

Section: Introductionmentioning

confidence: 99%

Robot navigation in unknown environment with obstacle recognition using laser sensor

Kumar

Vamossy

2019

IJECE

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<p>Robot navigation in unknown and dynamic environments may result in aimless wandering, corner traps and repetitive path loops. To address these issues, this paper presents the solution by comparing the standard deviation of the distance ranges of the obstacles appeared in the robot navigation path. For the similar obstacles, The standard deviations of distance range vectors, obtained from the laser range finder sensor of the robot at similar pose, are very close to each other. Therefore, the measurements of odometer sensor are also combined with the standard deviation to recognize the location of the obstacles. A novel algorithm, with obstacle detection feature, is presented for robot navigation in unknown and dynamic environments. The algorithm checks the similarity of the distance range vectors of the obstacles in the path and uses this information in combination with the odometer measurements to identify the obstacles and their locations. The experimental work is carried out using Gazebo simulator.</p>

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“…Researchers even exploited the use of hexapod to scale difficult terrain for successfully performing search and rescue operation [6]. The advancement in the allied areas has resulted in an amalgamation of swarm intelligence, mobility of robots and fuzzy logic [7].…”

Section: Introductionmentioning

confidence: 99%

Packet forwarding mechanism for mobile robots bounded by random walk model

Mathur

Dubey

2019

EAI Endorsed Trans IoT

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With the evolution of technology search and rescue operations are now been executed with the help of mobile robots. Wired mobile robot deployment is very cumbersome and constrained. Thus, the need arises for appropriate wireless technology that may support the same or even better functionality. ZigBee is gaining popularity as supporting technology to facilitate the working of mobile robots for search and rescue operations. This is because ZigBee based nodes utilize the industrial, scientific, and medical frequency band that supports a data rate up to 250 kbps. This paper presents a packet forwarding mechanism for ZigBee based mobile wireless sensor network nodes. The results achieved through the reported work shows that the packet loss rate comes around to be 2 percent resulting in a 98 percent successful packet reception at the receiver end.

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Obstacle avoidance and motion planning scheme for a hexapod robot Octopus-III

Cited by 68 publications

References 18 publications

Where Do I Move My Sensors? Emergence of a Topological Representation of Sensors Poses From the Sensorimotor Flow

Where Do I Move My Sensors? Emergence of a Topological Representation of Sensors Poses From the Sensorimotor Flow

Robot navigation in unknown environment with obstacle recognition using laser sensor

Packet forwarding mechanism for mobile robots bounded by random walk model

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