RobocupSoccer Humanoid League is one of the earliest soccer leagues in RoboCup competition. Since RoboCup Humanoid League’s debut in 2002, the teams under the League have seen remarkable advancement and also noticeable increase in the number of sci-tech achievements. KidSize Robot involves multiple basic disciplines and cutting-edge technologies, and its ultimate goal is not to accomplish the competition between robot soccer teams, but to achieve the contest between robot soccer teams and human soccer teams.

The competition of AdultSize Group is introduced for the first time, in which each robot is up to 165 centimeters tall, simulating full size and full-body freedom of human. Not only can the robot complete human-like movements such as turning the head and twisting the waist, but also achieve high dynamic response and difficult force control.

The RoboCup@home league aims to develop service and assistive robot technology with high relevance for future personal domestic applications. It is the largest international annual competition for autonomous service robots and is part of the RoboCup initiative.A set of benchmark tests is used to evaluate the robots abilities and performance in a realistic non-standardized home environment setting.Focus lies on the follwing domains but is not limited to: Human Robot Interaction and Cooperation, Navigation and Mapping in dynamic environments, Computer Vision and Object Recognition under natural light conditions, Object Manipulation, Adaptive Behaviors, Behaviors Integration, Ambient Intelligence, Standardization and System Integration. It is collocated with the RoboCup Symposium.

The RCAP CoSpace Grand Prix Challenge is a new educational initiative to interest, excite and engage participants regarding STEM and Computational Thinking through tinkering, making and coding in both virtual and real environments (CoSpace). In the RCAP CoSpace Grand Prix Challenge, students are tasked to make and code their own robot to take part in the Challenge. In the CoSpace Grand Prix Challenge, teams are required to make a robot, code a robot, and finally take part in the Robot Race in the real-virtual co-existing space. The robot race begins in the real world. It will notify its virtual team robot after it reaches the teleportation terminal. The virtual robot will continue the race in the virtual world to complete the course. Teams are required to develop appropriate strategies for both real and virtual autonomous robot.

In RCAP CoSpace Rescue Challenge, teams have to develop and program appropriate strategies for both real and virtual autonomous robots to navigate through real and virtual worlds to collect objects. The robot will compete with another team’s robot that is searching and collecting objects in the same real and virtual worlds, at the same time.In CoSpace Rescue, teams are required to build a real robot, develop and program appropriate strategies for both real and virtual autonomous robots to navigate through the real and virtual worlds and collect objects, while competing with another team’s robot that is searching and collecting objects in the same real and virtual worlds.

The RCAP CoSpace Autonomous Delivery (ADL) Challenge is blending mobile robots and supply chain management. Vehicle-road coordination system provided by CoSpace Autonomous Delivery platform allows participants from Secondary, Tertiary and University to better study AI problems such as path planning and dynamic planning. In RCAP CoSpace Autonomous Delivery Challenge, teams need to develop and program appropriate strategies for robots based on the Intelligent transportation system (ITS) provided by CoSpace platform. In the last mile delivery and smart city scenarios build by CoSpace, robots need to deliver parcels from Distribution Centre to Collection Station with maximum efficiency.

Centering on small unmanned aerial vehicles (UAV), the Aerial Manipulation Robot Challenge is an intelligent aerial robot competition developed and devised by the Tsinghua University team, and it is mainly used to test the technologies on UAV dense formation, precise high-speed obstacle avoidance, precise aerial positioning, target search, and aerial operation. A simulated chemical plant is built in the competition area, and several numbers are placed on simulated ladders, reaction towers, etc. Then, the UAV needs to search for the numbers within the chemical plant area by itself, and leverages the joystick or robotic arm to touch the numbers and get corresponding scores. The winner is the one with the highest score within given time.