In the era of rapid artificial intelligence development, human–agent collaboration holds the potential to significantly enhance work efficiency. While existing studies have explored various collaboration strategies and resource methods, there remains a notable lack of in-depth research on how to economically allocate a limited budget to acquire both human and agent computing capacities. To address this gap, we first construct a developer model based on theories from psychology and economics, providing a quantitative description of human working time and efficiency. Building upon this, we further investigate the impact of dynamic budget allocation strategies on consumer decision-making. Specifically, a novel budget recycling mechanism is introduced to redistribute unused resources, thereby enhancing system responsiveness. Experimental results demonstrate a 56% improvement in resource utilization and a 32% increase in task completion. This confirms the effectiveness of our proposed method in optimizing collaboration and supporting sustainable project execution.

Soft wall-climbing robots have been limited in their ability to perform complex locomotion in diverse environments due to their structure and weight. Thus far, soft wall-climbing robots with integrated functions that can locomote in complex 3-D environments are yet to be developed. This article addresses this challenge by presenting a lightweight (2.57 g) soft wall-climbing robot with integrated linear, turning, and transitioning motion capabilities. The soft robot employs three pneumatic bending actuators and two adaptive electroadhesion pads, which enable it to flip forward, transition between two walls, turn in two directions, and adhere to various surfaces. Different motion and control strategies are proposed based on a theoretical model. The experimental results demonstrate that the robot can move at an average speed of 3.85 mm/s (0.08 body length/s) on horizontal, vertical, and inverted walls and make transitions between walls with different pinch angles within 180°. Additionally, the soft robot can carry a miniature camera on vertical walls to perform detection and surveillance tasks. This article provides a reliable structure and control strategy to enhance the multifunctionality of soft wall-climbing robots and enable their applications in unstructured environments.