Abstract: In order to solve the poor intelligence and universality problems of the home service robot with traditional knowledge-based or learning-based service cognitive mechanisms, an autonomous cognition and development system of robot service tasks based on a composite framework combining incremental hierarchical discriminant regression (IHDR) algorithm with BP (backpropagation) neural network is constructed. A large amount of sample data are collected for learning and development of robots based on the technical support provided by multiple sensors in intelligent space and Internet of Things (IoT). On this basis, a modified IHDR algorithm is designed in light of the mixing characteristics of these sample data to achieve cluster updating and response calculation for mixed-type sample data, and an IHDR tree is constructed as the "brain" of robot to store its historical experience, which will provide historical experience for robot to learn and judge, realizing autonomous cognition of services. The JSHOP2 (Java simple hierarchical planner) is used to decompose the cognized complex tasks to obtain atomic tasks which can be directly executed by the robot. Meanwhile, a service cognition algorithm based on BP neural network is developed to avoid the limitation of IHDR tree size. The BP neural network is trained with sample data to map the actual scene in intelligent space to the service required by user, and thus the robot can still make service decisions autonomously based on BP neural network in case that the IHDR tree can't provide historical experience. Next, the IHDR tree is updated incrementally with the mapping result, enriching the robot's experience and knowledge, and realizing the development of autonomous cognitive ability for robot service. The simulation results show that the accuracy and developmental ability of cognition for services required by the user are improved for the service robot in intelligent space by the composite framework, which may promote the realization of man-machine communion.