The BARN Challenge aims at evaluating state-of-the-art autonomous navigation systems to move robots through highly constrained environments in a safe and efficient manner. The task is to navigate a standardized Clearpath Jackal robot from a predefined start to a goal location as quickly as possible without any collision. The challenge will take place both in the simulated BARN dataset and in physical obstacle courses at ICRA2024.

URL:　https://cs.gmu.edu/~xiao/Research/BARN_Challenge/BARN_Challenge24.html

The Robotic Sim2Real Competition is designed to bridge the gap between simulation and reality. It aims to foster creativity, innovation, and interdisciplinary collaboration among university students and researchers by encouraging them to translate their simulation-based research into practical, real-world applications, empowering the robots
to autonomously make decisions, maneuver, and execute grasping actions.

The Robotic Sim2Real Competition has been uninterruptedly held by our organization team, AIR (Institute for AI Industry Research, Tsinghua University), at ICRA for 2 years. Sim2Real 2024 consists of two independent challenges: the AgileX Sim2real Challenge of the plates arranging task and the RoboMaster University Sim2Real Challenge of the mineral searching task.

URL: http://sim2real.net/

In the rapidly evolving domain of autonomous driving, the accuracy and resilience of perception systems are paramount. Recent advancements, particularly in bird’s eye view (BEV) representations and LiDAR sensing technologies, have significantly improved in-vehicle 3D scene perception.
Yet, the robustness of 3D scene perception methods under varied and challenging conditions — integral to ensuring safe operations — has been insufficiently assessed. To fill in the existing gap, we introduce the RoboDrive Challenge @ ICRA 2024, seeking to push the frontiers of robust autonomous driving perception.
RoboDrive is one of the first benchmarks that targeted probing the Out-of-Distribution (OoD) robustness of state-of-the-art autonomous driving perception models, centered around two mainstream topics: common corruptions and sensor failures.
There are five tracks in this RoboDrive Challenge, with emphasis on the following 3D scene perception tasks:

Track 1: Robust BEV Detection.
Track 2: Robust Map Segmentation.
Track 3: Robust Occupancy Prediction.
Track 4: Robust Depth Estimation.
Track 5: Robust Multi-Modal BEV Detection.

For additional implementation details, kindly refer to our RoboBEV, RoboDepth, and Robo3D projects.

URL: https://robodrive-24.github.io

Food Topping Challenge(FTC) is robotic contest mainly supported by the food sample standard working group of RSJ (The Robotics Society of Japan). The ICRA2024 FTC is the first event in a series of challenges that will evolve from AI vision and robot arm for food picking and placement. The contest will be evaluated technical challenge of picking number of foods, technical demonstration of artistic impression of food topping for sushi bowl as ikura don.
The FTC has great potential to lead the robotics community in technology advancement, foodtech field engineers, and foster interactions with industries, ultimately leading to the creation of practical services for the essential workers.
Click here for Competition Website https://icra2024.rt-net.jp/
Click here for Competition Registration Already Closed(Deadline Jan.31 2024)
Related Workshop https://sites.google.com/view/icra2024cookingrobotics/
Competition Key Dates :
14, 15 MAY 2024 – Practice Day
16 MAY 2024 – Competition Day
17 MAY 2024 – Related workshop “Cooking Robotics” https://sites.google.com/view/icra2024cookingrobotics/

URL: https://icra2024.rt-net.jp/

Minidrone Competition is an excellent opportunity for students to get an introduction to Model-Based Design while challenging their peers. Student Teams are expected to design a line follower algorithm using Simulink. In the process, students get to learn how to model, simulate, and fly a minidrone.

The competition consists of two rounds, with the first focusing on algorithm development within Simulink for the specified Parrot model, and the finals allowing shortlisted teams to showcase their algorithms by deploying them into a Parrot Mambo Minidrone at ICRA 2024.

URL:　https://in.mathworks.com/academia/student-competitions/minidrones/icra.html

The IEEE RAS Quadruped Robot Challenges (QRC) are competitions that focus on advancing robotic technology in unstructured environments. The challenges progress from remote-controlled to autonomous navigation of robots over various terrains and obstacles, culminating in mobile manipulation tasks.

The qualification round is conducted remotely worldwide, with finals in Yokohama, Japan. The event aims to foster technological advancement, set industry standards, and improve the deployment of robots in real-world scenarios.

Click here for Competition Registration and participation: https://ieee-qrc.agilertc.com/

URL:https://rise.skku.edu/qrc2024

The Bots & Bento Challenge, a joint initiative by Olive Robotics GmbH, UTokyoIPC, and TUM Venture Lab Robotics / AI, tasks teams with employing hardware and software tools to build and program robots for pallet handling tasks. Participants will design and construct mobile robots using provided ROS-based kits (Yes, each team will get the necessary hardware parts during the competition), aiming to efficiently transport KLT standard pallets loaded with Bento to specified locations (pallets and places are marked with AR Tag). This competition emphasizes autonomous material handling, promoting creativity, practical skills development, and the opportunity for contenders to demonstrate their capabilities in an engaging and collaborative environment.
Rule book URL: https://github.com/olive-robotics/bots_bento_icra24

URL: https://www.tum-venture-labs.de/education/bots-bento-the-first-robotic-pallet-handler-competition-icra-2024/

The teams participating in the 15th F1TENTH Grand Prix at ICRA 2022 will build a 1:10 scaled autonomous race car according to a given specification and write software for it to fulfill the objectives for the competition: race head-to-head, Don’t crash, and minimize lap time. Each team will bring its own physical F1TENTH car with its own written software. The organizers provide the race setup (rules, submissions, guidelines), the track, and related infrastructure, as well as organize the race itself.

URL: https://icra2024-race.f1tenth.org/

The purpose of this competition is to enhance the quality of customer service through intelligent robots in environments such as retail stores and shopping malls and to realize new service forms. This competition, therefore, focuses on the ability to engage in natural and friendly communication in customer service based on intention recognition, natural language understanding, conversation control, conversation for ambiguity resolution, and so on.
Additionally, this competition has a unique structure where robots in virtual space converse with humans in real space. Proposals contributing to the realization of new services through the fusion of metaverses, digital twins, cyber-physical systems, and social robotics are welcome.

URL: https://sites.google.com/view/fcsc-cyberspace/home

URL: https://www.cse.usf.edu/~yusun/rgmc/2024.html

The purpose of this competition is to harness the power of crowdsourcing and cutting-edge LiDAR sensors to create highly detailed and up-to-date 3D maps of large-scale areas. Up-to-date and accurate maps of large-scale environments are essential for informed decision-making, urban planning, environmental monitoring, and responding to emerging challenges. By advancing crowdsourced mapping techniques, we can unlock new opportunities for sustainable development, resource management, and disaster preparedness.

URL: https://metaslam.github.io/competitions/icra2024/