Concurrently evolving sensor morphology and control for a hexapod robot

Parker, G.B.; Nathan, P.J.

doi:10.1109/cec.2010.5586233

Cited by 5 publications

(6 citation statements)

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“…Despite these highly stimulating works, the role of the size, shape and placement of the sensors, commonly known as sensor morphology, does not seem to have been thoroughly investigated. While the importance of sensor morphology in determining the sensing characteristics and performance has gained a lot of attention in biology [ 24 , 25 ], embodied intelligence [ 26 ], and most recently in robotics [ 27 , 28 ], its role in soft body sensing still remains as a challenge. The sensorization solutions so far have had the potential for enabling customizable sensor morphology, but required complex molding and suggested casting processes for integration [ 13 , 29 ] or realized commonly used sensor morphologies [ 30 , 31 ].…”

Section: Introductionmentioning

confidence: 99%

SVAS3: Strain Vector Aided Sensorization of Soft Structures

Çulha

Nurzaman

Clemens

et al. 2014

Sensors

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Soft material structures exhibit high deformability and conformability which can be useful for many engineering applications such as robots adapting to unstructured and dynamic environments. However, the fact that they have almost infinite degrees of freedom challenges conventional sensory systems and sensorization approaches due to the difficulties in adapting to soft structure deformations. In this paper, we address this challenge by proposing a novel method which designs flexible sensor morphologies to sense soft material deformations by using a functional material called conductive thermoplastic elastomer (CTPE). This model-based design method, called Strain Vector Aided Sensorization of Soft Structures (SVAS3), provides a simulation platform which analyzes soft body deformations and automatically finds suitable locations for CTPE-based strain gauge sensors to gather strain information which best characterizes the deformation. Our chosen sensor material CTPE exhibits a set of unique behaviors in terms of strain length electrical conductivity, elasticity, and shape adaptability, allowing us to flexibly design sensor morphology that can best capture strain distributions in a given soft structure. We evaluate the performance of our approach by both simulated and real-world experiments and discuss the potential and limitations.

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Section: Introductionmentioning

confidence: 99%

SVAS3: Strain Vector Aided Sensorization of Soft Structures

Çulha

Nurzaman

Clemens

et al. 2014

Sensors

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“…optimizing the thickness of convex lens to minimize ray scattering [91]. However, as also shown by examples [33,34,[80][81][82][83][84][85], there are more aspects to consider in the problem of optimizing sensor morphology from bioinspired robotics perspective, such as co-optimization between motor control and morphology, gaps between simulation and real-world implementation, or how factors such as material properties or multiagent setting affect the design (see [92] for a review of the current progress of evolutionary algorithm applications rsfs.royalsocietypublishing.org Interface Focus 6: 20160016 in robotics), which also shows the importance of an integrative view.…”

Section: Adaptation Over Multiple Timescalesmentioning

confidence: 96%

“…the type of the sensed physical phenomenon, such as visual (light) [20 -27,32,33,35-46], somatosensory (touch and perception) [47,48,49,[50][51][52][53][54][55][56][58][59][60][61][62][63][64][65][66][67][68], auditory (hearing) [71,72] and even electric [73][74][75][76][77] or magnetic field [78,79]. Some researchers also investigated sensor morphology of multimodal systems, where a combination of multiple sensors is used, each sensing a different physical phenomenon [80][81][82][83][84].…”

Section: The Research Landscapementioning

confidence: 99%

“…Finally, without any specific corresponding biological systems, evolutionary algorithm was commonly used to couple motor control and sensor morphology [33,66,[80][81][82][83][84]]. An example is shown in [66], where the speed level and positions of single bit contact sensors mounted on a mobile robot are co-optimized to accomplish a collision free navigation task in a cluttered environment.…”

Section: Morphology For Active Sensing and Sensory Motor Coordinationmentioning

confidence: 99%

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Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

Iida

Nurzaman

2016

Interface Focus.

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Sensor morphology, the morphology of a sensing mechanism which plays a role of shaping the desired response from physical stimuli from surroundings to generate signals usable as sensory information, is one of the key common aspects of sensing processes. This paper presents a structured review of researches on bioinspired sensor morphology implemented in robotic systems, and discusses the fundamental design principles. Based on literature review, we propose two key arguments: first, owing to its synthetic nature, biologically inspired robotics approach is a unique and powerful methodology to understand the role of sensor morphology and how it can evolve and adapt to its task and environment. Second, a consideration of an integrative view of perception by looking into multidisciplinary and overarching mechanisms of sensor morphology adaptation across biology and engineering enables us to extract relevant design principles that are important to extend our understanding of the unfinished concepts in sensing and perception.

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“…In robotics research, there are several attempts to exploit this interdependence in order to accomplish different kinds of sensing tasks with suitable performance. For example, it has been shown that concurrently evolving the sensors placement and the motion control significantly improve the effectiveness of hexapod robot navigation [ 13 ]. In multi-robot setting, the interdependence between sensor morphology and the motion of each robot has also been studied in a context of formation control [ 14 ].…”

Section: Introductionmentioning

confidence: 99%

Active Sensing System with In Situ Adjustable Sensor Morphology

et al. 2013

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BackgroundDespite the widespread use of sensors in engineering systems like robots and automation systems, the common paradigm is to have fixed sensor morphology tailored to fulfill a specific application. On the other hand, robotic systems are expected to operate in ever more uncertain environments. In order to cope with the challenge, it is worthy of note that biological systems show the importance of suitable sensor morphology and active sensing capability to handle different kinds of sensing tasks with particular requirements.MethodologyThis paper presents a robotics active sensing system which is able to adjust its sensor morphology in situ in order to sense different physical quantities with desirable sensing characteristics. The approach taken is to use thermoplastic adhesive material, i.e. Hot Melt Adhesive (HMA). It will be shown that the thermoplastic and thermoadhesive nature of HMA enables the system to repeatedly fabricate, attach and detach mechanical structures with a variety of shape and size to the robot end effector for sensing purposes. Via active sensing capability, the robotic system utilizes the structure to physically probe an unknown target object with suitable motion and transduce the arising physical stimuli into information usable by a camera as its only built-in sensor. Conclusions/SignificanceThe efficacy of the proposed system is verified based on two results. Firstly, it is confirmed that suitable sensor morphology and active sensing capability enables the system to sense different physical quantities, i.e. softness and temperature, with desirable sensing characteristics. Secondly, given tasks of discriminating two visually indistinguishable objects with respect to softness and temperature, it is confirmed that the proposed robotic system is able to autonomously accomplish them. The way the results motivate new research directions which focus on in situ adjustment of sensor morphology will also be discussed.

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Concurrently evolving sensor morphology and control for a hexapod robot

Cited by 5 publications

References 8 publications

SVAS3: Strain Vector Aided Sensorization of Soft Structures

SVAS3: Strain Vector Aided Sensorization of Soft Structures

Adaptation of sensor morphology: an integrative view of perception from biologically inspired robotics perspective

Active Sensing System with In Situ Adjustable Sensor Morphology

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