Intelligent Terrain Mapping with a Quadruped Spider Robot: A Bluetooth-Enabled Mobile Platform for Environmental Reconnaissance

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m2 demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics.

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Publication Details

Journal
Automation
Published
2025-09-24
DOI
https://doi.org/10.3390/automation6040050
Primary Topic
Modular Robots and Swarm Intelligence
Type
article
Field-Weighted Citation Impact
0.00

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article

Intelligent Terrain Mapping with a Quadruped Spider Robot: A Bluetooth-Enabled Mobile Platform for Environmental Reconnaissance

Kanad Ray, M. Shamim Kaiser, Sandeep Gupta
Automation
Modular Robots and Swarm Intelligence
article

Intelligent Terrain Mapping with a Quadruped Spider Robot: A Bluetooth-Enabled Mobile Platform for Environmental Reconnaissance

Kanad Ray, M. Shamim Kaiser, Sandeep Gupta
article en

Abstract

This paper introduces a new quadruped spider robot platform specializing in environmental reconnaissance and mapping. The robot measures 180 mm × 180 mm × 95 mm and weighs 385 g, including the battery, providing a compact yet capable platform for reconnaissance missions. The robot consists of an ESP32 microcontroller and eight servos that are disposed in a biomimetic layout to achieve the biological gait of an arachnid. One of the major design revolutions is in the power distribution network (PDN) of the robot, in which two DC-DC buck converters (LM2596M) are used to isolate the power domains of the computation and the mechanical subsystems, thereby enhancing reliability and the lifespan of the robot. The theoretical analysis demonstrates that this dual-domain architecture reduces computational-domain voltage fluctuations by 85.9% compared to single-converter designs, with a measured voltage stability improving from 0.87 V to 0.12 V under servo load spikes. Its proprietary Bluetooth protocol allows for both the sending and receiving of controls and environmental data with fewer than 120 ms of latency at up to 12 m of distance. The robot’s mapping system employs a novel motion-compensated probabilistic algorithm that integrates ultrasonic sensor data with IMU-based motion estimation using recursive Bayesian updates. The occupancy grid uses 5 cm × 5 cm cells with confidence tracking, where each cell’s probability is updated using recursive Bayesian inference with confidence weighting to guide data fusion. Experimental verification in different environments indicates that the mapping accuracy (92.7% to ground-truth measurements) and stable pattern of the sensor reading remain, even when measuring the complex gait transition. Long-range field tests conducted over 100 m traversals in challenging outdoor environments with slopes of up to 15° and obstacle densities of 0.3 objects/m2 demonstrate sustained performance, with 89.2% mapping accuracy. The energy saving of the robot was an 86.4% operating-time improvement over the single-regulator designs. This work contributes to the championing of low-cost, high-performance robotic platforms for reconnaissance tasks, especially in search and rescue, the exploration of hazardous environments, and educational robotics.

AutomationVol. 6(4)
Amity University (AE), Poornima University (IN), Jahangirnagar University (BD)
Department of Artificial Intelligence, Korea University
Openalex Percentile: Top 73%
Modular Robots and Swarm Intelligence
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