ISRO Robotic Challenge - URSC 2026

ISRO Robotics Challenge-URSC 2024 & 2025 (IRoC-U 2024 & 2025) provided an opportunity to the student community to showcase their engineering problem solving capabilities for space missions. The student community responded with great enthusiasm and its unprecedented success served as an inspiration for the next challenge IRoC-U 2026.

The Honourable Prime Minister of India appreciated and praised ISRO’s initiatives such as the Indian Space Hackathon and the Robotics Challenge (IRoC-U), noting that these efforts help to kindle greater interest in space among the youth. He warmly congratulated all the students who participated in these competitions and the winners for their creativity and enthusiasm.

One of ISRO’s future goal is the exploration of Martian surface and as a part of Martian surface exploration an Autonomous Unmanned Aerial Vehicle (UAV) will carry out scientific activities. ISRO solicits from the youth of India innovative ideas and designs in the area of navigation for future missions through the conduct of Robotics Challenge.

The IRoC-U 2026 challenges the students to develop “Towards Swarm Expedition: Autonomous Surveyor Challenge for Exploration, Navigation and Dynamics (ASCEND)” without any external navigation aids like GNSS, pseudolite or reflector arrays.

IRoC-U 2025 challenge consisted of demonstration of autonomous, aerial capability without GPS aid. IRoC-U 2026 challenge will involve autonomous navigation, landing, power transfer and image data validation. As a result, this year’s challenge advances and refines the goals defined in the last year.

Autonomous aerial swarms are the future of planetary exploration: they can deploy, survey, recharge and share data without direct human control. The “Towards Swarm Expedition: Autonomous Surveyor Challenge for Exploration, Navigation and Dynamics (ASCEND)” takes the first step toward this vision. In this challenge, teams will build a micro-UAV (aerial vehicle) and a base station. The UAV departs from its base station, acquires the target characteristics it needs to identify, searches a designated area for those features, then returns to base station, transfer its data, and recharge - all without GPS, telemetry or remote piloting.

Hence, the current challenge focuses on developing and demonstrating navigation and guidance techniques rather than building aerial vehicles. Students can use/develop any available (off-the-shelf) aerial vehicle complying with existing DGCA rules.

The student community needs to develop and demonstrate the autonomous capabilities of ASCEND:

1.  for navigation and guidance without any external navigation aids
2.  to deploy, survey, recharge and share data without direct human control
3.  to search for pre-defined arena for target features, return to base station to land and transfer data and recharge its power system.
4.  Base station should support data transfer and charging through wired and/or wireless interfaces. If wired operation is used, the interface should have ports for i) image data transfer and ii) charging. The images (target features) captured by ASCEND during survey need to be transferred to base station and compared with the reference feature database for validation
5.  Manual human intervention or manual alignment during the task is not permitted.

ASCEND has to perform the following tasks during the various rounds of the challenge:

• Seeding Task: While within the yellow-boundary base zone, the UAV must autonomously capture the provided seed images (3-5 sample feature images) supplied through the interface of the base station.
• Search Task: The UAV departs from the base station and autonomously searches the arena to locate unknown instances of the seeded feature types (for example: layered rock formations, red-oxide patches, reflective ice-like patches etc.) - each feature type has 2 to 3 instances present in the arena.
• Detection & Documentation Task: On detecting a feature instance, the UAV records its local estimated coordinates (relative to the base station frame) and captures a verification image of the feature.
• Return Task: The UAV returns to the base station, lands and interfaces without human intervention and initiates data transfer (images and coordinate log) via wired or wireless mode. At the same time, the bay charges the UAV for the next sortie. 
• Validation Task: The base station computer validates the transferred images against the seed images (automatic image-matching). If valid, that detection counts towards the successful sortie.
• Repeat sorties: The teams can attempt multiple sorties for completing the task. The merit is considered based on the number of sorties.

Refer the rule book for the details. Rule book will be updated from time to time as the challenge rounds progress. The participants are requested to follow the latest version of the rulebook available in the web portal.