Grant: Discovery Grants Program - Individual

The past decade has witnessed the increasing demands from industry for using robots in the inspection of mechanical structures. However, small, confined areas of some complex mechanical structures brings challenges for using industrial robots to perform inspections considering reliability, efficiency and manoeuvrability. Bio-inspired robots, mimicking the behaviors of some animals to maintain a dynamically balanced system, provide solutions to some of these issues, thus, becoming a research trend recently. This research proposal is targeting to address the current hurdles of using robots for inspection: poor manoeuvrability, low efficiency and limited working areas. A typical example is the inspection of underwater marine structures or airframe structures with confined areas. Due to the limited access and complexity of structures with obstacles and holes, the structure inspection is still highly dependent on human operators nowadays. This research program proposes the design of a multilegged bio-inspired robot for the purpose of inspection of complex mechanical structures with confined areas and data collection. The inspection robot is expected to move deeply into the structure under inspection with high manoeuvrability and obstacle avoidance capability. The proposed research is composed of mechanism design, sensing system and control methodology. Innovative transmission system, based on our previous transmission system design for mobile robots at the Centre for Intelligent Machines at McGill University, is proposed to realize mobility of three for each leg of the robot. By doing this, the proposed inspection robot would have significant advantages over the current multilegged robots on the market in improving manoeuvrability to carry out locomotion over rough terrain and avoid obstacles. The micro-scale sensing system, using the state-of-the-art MEMS fabrication technology, is expected to yield the accurate information of pose-position and orientation-and its twist-point velocity and angular velocity of robot undergoing 3D motions. This research will also propose developing an intelligent control methodology based on neural networks and genetic algorithms. The proposed robot design will be integrated with underwater vehicles, to realize fully autonomous data collection for ocean engineering purposes. Through close collaboration with diverse research groups, the theoretical developments of the proposed research are expected to serve a wide range of scientific and industrial sectors, including underwater navigation and data collection, oil pipeline inspection and airframe structure inspection. It is expected that the proposed research program will result in fruitful publications with significant impact and training 3 PhD and 2 Master's students as part of this program.