Software / AI

We covered learning in AI in this post. After learning is complete, there is the reasoning, decision making and planning stage. In short, after an AI model extracts information from data and learns, it applies this knowledge for reasoning. Then it decides a course of action, which is the decision making part. And finally, it plans the consecutive actions, which is the planning part. Now lets explain each a little bit more: We can classify reasoning into three categories: Symbolic Reasoning Probabilistic Reasoning Neural or Learned Reasoning Let’s explain each a little more: Symbolic reasoning, which is also called as Logic-Based or Rule-based reasoning, is the oldest method. It operates […] Read More

We can divide learning of AI, which is called the Machine Learning (ML) into the following categories: Supervised Learning Unsupervised Learning Reinforcement Learning Hybrid / Newer Methods A humanoid robot’s learning, although still falls under the main categories above, is quite different than an AI model that exists only as an algorithm because in the case of humanoid robot we have the data input that comes through physical sensors. In this case therefore, we have what is called the “physical AI”. The sensors we talked about in humanoid robots sensors post here, all come into play, to give robot a coherent understanding and awareness of itself and its surroundings. Now […] Read More

Control systems in a humanoid robot serve as the layer between the main AI system (that is responsible from the overalllearning, planning, reasoning and decision making of a robot) and the hardware that will enable robot’s actions. According to the “order” given by the AI, the control system then executes this order, while at the same time coordinating all systems within the robot. The highest control level is where the control system interacts with the AI. The middle control system controls overall posture and movement and the low level control systems controls joints (actuators) and sensors and processes sensor feedback. Let’s take a look at each. High Level Controls: High […] Read More

Analysis of Sensor Data A humanoid robot receives information about its surroundings and also about its own state at a given time and location through its sensors. This information is then used to decide the proper course of action accordingly and then executing these decisions. Sensor inputs are often analyzed as combined inputs in order to obtain better overall information and improve accuracy. There are various important aspects to sensor data analysis, such as time dependence, filtering noise, extraction of useful data, classification of data. See our post here for more detail on this topic. Cognitive AI Cognitive AI encompasses perception, reasoning, learning, decision making and planning, which are all […] Read More