Millimeter-Wave Sensing for Avoidance of High-Risk Ground Conditions for Mobile Robots

Mobile robot autonomy has made significant advances in recent years, with navigation algorithms well developed and used commercially in certain well-defined environments, such as warehouses. The common link in usage scenarios is that the environments in which the robots are utilized have a high degree of certainty. Operating environments are often designed to be robot friendly, for example augmented reality markers are strategically placed and the ground is typically smooth, level, and clear of debris. For robots to be useful in a wider range of environments, especially environments that are not sanitized for their use, robots must be able to handle uncertainty. This requires a robot to incorporate new sensors and sources of information, and to be able to use this information to make decisions regarding navigation and the overall mission. When using autonomous mobile robots in unstructured and poorly defined environments, such as a natural disaster site or in a rural environment, ground condition is of critical importance and is a common cause of failure. Examples include loss of traction due to high levels of ground water, hidden cavities, or material boundary failures. To evaluate a non-contact sensing method to mitigate these risks, Frequency Modulated Continuous Wave (FMCW) radar is integrated with an Unmanned Ground Vehicle (UGV), representing a novel application of FMCW to detect new measurands for Robotic Autonomous Systems (RAS) navigation, informing on terrain integrity and adding to the state-of-the-art in sensing for optimized autonomous path planning. In this paper, the FMCW is first evaluated in a desktop setting to determine its performance in anticipated ground conditions. The FMCW is then fixed to a UGV and the sensor system is tested and validated in a representative environment containing regions with significant levels of ground water saturation.

Bio-inspired Multi-robot Autonomy

Increasingly, high value industrial markets are driving trends for improved functionality and resilience from resident autonomous systems. This led to an increase in multi-robot fleets that aim to leverage the complementary attributes of the diverse platforms. In this paper we introduce a novel bio-inspired Symbiotic System of Systems Approach (SSOSA) for designing the operational governance of a multi-robot fleet consisting of ground-based quadruped and wheeled platforms. SSOSA couples the MR-fleet to the resident infrastructure monitoring systems into one collaborative digital commons. The hyper visibility of the integrated distributed systems, achieved through a latency bidirectional communication network, supports collaboration, coordination and corroboration (3C) across the integrated systems. In our experiment, we demonstrate how an operator can activate a pre-determined autonomous mission and utilize SSOSA to overcome intrinsic and external risks to the autonomous missions. We demonstrate how resilience can be enhanced by local collaboration between SPOT and Husky wherein we detect a replacement battery, and utilize the manipulator arm of SPOT to support a Clearpath Husky A200 wheeled robotic platform. This allows for increased resilience of an autonomous mission as robots can collaborate to ensure the battery state of the Husky robot. Overall, these initial results demonstrate the value of a SSOSA approach in addressing a key operational barrier to scalable autonomy, the resilience.