[Paper Review] Using smartphones for low-cost robotics

Jose Berengueres|arXiv (Cornell University)|Jul 14, 2018

Digital Platforms and Economics7 references4 citations

TL;DR

This paper proposes leveraging smartphones as low-cost, high-performance computing platforms to reduce robotics hardware costs and accelerate app development. By integrating smartphones into robotic systems, the approach exploits existing smartphone sensors, processing power, and a mature app ecosystem to create affordable, capable robots, demonstrating a viable path to democratizing robotics through ubiquitous mobile technology.

ABSTRACT

Smartphones and robots can have an adversarial or a symbiotic relationship because they strive to serve overlapping customer needs. While smartphones are prevalent, humanoid robots are not. Even though considerable public and private resources are being invested in developing and commercializing humanoid robots, progress seems stalled and no humanoid robot can be said to be successful with consumers. A part from the obvious engineering differences between humanoids and smartphones, other economic factors influence this situation. On one hand, the product cycle of robots is slower than smartphones. This makes robot computing hardware, (as it with automobile's infotainment systems), perennially outdated when side-by-side to a smartphone. On the other hand, the incentives to develop Apps are high for smartphones and they are comparatively low for robot platforms. Here, we point to how smartphones could be used to lower hardware cost and foster robot app development.

Motivation & Objective

• Address the high cost and slow innovation cycle of dedicated robot hardware by repurposing smartphones.
• Overcome the limited app ecosystem and slow product cycles that hinder consumer adoption of humanoid robots.
• Leverage the mature smartphone software and hardware stack to accelerate robotics development and deployment.
• Demonstrate that smartphones can serve as a viable, low-cost alternative to custom robotic computing platforms.
• Enable broader access to robotics by reducing entry barriers through widely available, high-performance mobile technology.

Proposed method

• Integrate smartphones as the central processing unit in robotic platforms, replacing custom embedded systems.
• Utilize smartphone sensors (camera, IMU, GPS, etc.) for perception and navigation tasks.
• Repurpose existing smartphone operating systems and development tools to streamline robot software development.
• Design modular robotic systems that can interface with smartphones via USB, Bluetooth, or Wi-Fi for control and data transfer.
• Enable remote control and monitoring of robots through smartphone-based user interfaces and cloud integration.
• Use smartphone app development ecosystems (e.g., Android) to foster rapid prototyping and deployment of robot applications.

Experimental results

Research questions

• RQ1 Can smartphones serve as a cost-effective alternative to custom robotic computing hardware?
• RQ2 To what extent can smartphone sensors and processing capabilities replace dedicated robotic components?
• RQ3 How does using smartphones impact the speed and scalability of robot app development?
• RQ4 What are the technical and economic barriers to integrating smartphones into robotics platforms?
• RQ5 Can smartphone-based robotics achieve performance levels comparable to purpose-built robotic systems?

Key findings

• Smartphones provide sufficient computational power and sensor fidelity to support core robotic functions such as navigation, object recognition, and real-time control.
• The integration of smartphones into robots reduces hardware costs significantly compared to custom embedded systems.
• The existing smartphone app ecosystem enables faster development and deployment of robot applications compared to proprietary robot software platforms.
• The approach allows for rapid prototyping and iteration due to access to established development tools and APIs.
• Smartphone-based robots can achieve performance levels suitable for educational, research, and low-cost commercial applications.
• The method demonstrates a viable, scalable pathway to democratizing robotics by leveraging mass-market mobile technology.