Current Augmented Reality devices rely heavily on real-time environment mapping to provide convincing world-relative experiences through user interaction with virtual content integrated into the real world. This mapping is obtained and updated through many different algorithms, but often results in holes and other mesh artifacts when generated in less ideal scenarios, like outdoors and with fast movement. In this work, we present the Interaction-Triggered Estimation of AR Object Placement on Indeterminate Meshes, a quick, interaction-triggered method to estimate the normal and position of missing mesh pieces in real-time with low computational overhead. We achieve this by extending the user's hand using a group of additional raycast sample points, aggregating results according to different algorithms, and then using the resulting values to place an object. This thesis will first cover problems with current mapping techniques, thoroughly explain the rationale and algorithms behind our method, and then evaluate our method using a user study. / Master of Science / Augmented Reality (AR) technologies have the potential to change all our lives for the better through tight and seamless integration into our daily lives. Crucial to this seamless integration is the ability for users to manipulate virtual AR objects and interact effortlessly with real-world features around them. In order to facilitate this interaction, AR devices often create 3D maps of the real world to allow the device to recognize and respect the geometry of the world around it. Unfortunately, many AR devices still have trouble creating and maintaining these maps in challenging environments, like outdoors or when moving fast, so the resulting 3D maps of the environments have holes and inaccuracies, causing user interaction with the environment to be unreliable and breaking the seamless integration. While many solutions look toward more advanced algorithms that require more specialized sensors or next-gen AR devices to improve this mapping issue, we see an opportunity to enhance any existing 3D maps using a novel interaction aggregation approach that can theoretically work with any mapping technology. In this work, we present the Interaction-Triggered Estimation of AR Object Placement on Indeterminate Meshes, a work-in-progress application providing a quick, interaction-triggered method to estimate the normal and position of missing mesh in real-time with low computational overhead.