Abstract: A dynamic target tracking method for a robot having multiple joints includes: obtaining a motion state of a tracked dynamic target in real time; performing motion prediction according to the motion state at a current moment to obtain a predicted position of the dynamic target; performing lag compensation on the predicted position to obtain a compensated predicted position; performing on-line trajectory planning according to the compensated predicted position to obtain planning quantities of multi-step joint motion states at multiple future moments, and determining a multi-step optimization trajectory according to the planning quantities and a multi-step optimization objective function; and controlling the joints of the robot to according to the multi-step optimization trajectory.

Abstract: A collision detection method, a storage medium, and a robot are provided. The method includes: calculating an external torque of a first joint of the robot based on a preset generalized momentum-based disturbance observer; calculating an external torque of a second joint of the robot based on a preset long short-term memory network; calculating an external torque of a third joint of the robot based on the external torque of the first joint and the external torque of the second joint; and determining whether the robot has collided with an external environment or not based on the external torque of the third joint and a preset collision threshold. In the present disclosure, the component of the model error in the joint external torque calculated by the disturbance observer is eliminated to obtain the accurate contact torque, thereby improving the accuracy of the collision detection.

Abstract: A robot obstacle avoidance method, a robot controller using the same, and a storage medium are provided. The method includes: determining an influence value of an obstacle on a motion range of a joint of the robot according to a position of the obstacle in a workspace of the robot; establishing a state transition relationship of the robot by taking a joint velocity of the robot as a control target and a joint angular velocity of the robot as a control input quantity; and avoiding the robot from colliding with the obstacle during a movement process of the robot by performing a model predictive control on the robot according to the state transition relationship and the influence value. In the present disclosure, the influence of the obstacle on the motion range of the joint of the robot is fully considered.

Abstract: A method for controlling a robot comprising an end effector includes: establishing at steady state between the end effector and a working surface through a preset impedance control mechanism, and adjusting a contact force between the end effector and the working surface according to a preset desired force; obtaining a contact torque generated by the contact force; controlling the end effector to rotate according to the contact torque until a pose of the end effector is consistent with a pose of the working surface; and controlling the end effector to move tangentially along the working surface.

Abstract: A path planning method and a biped robot using the same are provided. The method includes: generating a candidate node set for a next foot placement based on a biped robot's own parameters and joint information of a current node, adding valid candidate nodes in the candidate node set to a priority queue so as to select optimal nodes for realizing next node expansion. These optimal nodes are output to generate a foot placement sequence from an initial node to a target node, which can greatly reduce the search amount for path nodes when the robot's legs intersect and touch the ground, thereby improving the efficiency of path planning.

Abstract: The present disclosure provides a robotic arm control method as well as an apparatus and a terminal device using the same. The method includes: obtaining a current joint angle of each of M joints of the robotic arm; obtaining a reference included angle based on the current joint angle of each of the M joints of the robotic arm; determining an expected included angle corresponding to the robotic arm within a target angle range based on the reference included angle and the preset included angle related evaluation function; and controlling the robotic arm based on the target joint angles of the M joints.

Abstract: Techniques and constructs to facilitate semantic matching and automated annotation (SMA) of attributes can take entity names and a keyword describing an attribute associated with the named entities as input and leverage a corpus of data such as data from tables, which can include HTML web tables, to automatically populate values associated with the named entities for the attribute. The constructs enable accurate SMA of attributes, such as attributes that relate to the entity and include numeric values in a different unit than the query, in a different scale than the query, and/or reflecting a time different from that of the query. An entity augmentation application programming interface (API) may be used to accept queries that include numeric criteria, parameters, or arguments, including query attributes represented by numeric values, which may be in different units or scales, and attributes represented by numeric values that can vary by time.

Abstract: Techniques and constructs to facilitate semantic matching and automated annotation (SMA) of attributes can take entity names and a keyword describing an attribute associated with the named entities as input and leverage a corpus of data such as data from tables, which can include HTML web tables, to automatically populate values associated with the named entities for the attribute. The constructs enable accurate SMA of attributes, such as attributes that relate to the entity and include numeric values in a different unit than the query, in a different scale than the query, and/or reflecting a time different from that of the query. An entity augmentation application programming interface (API) may be used to accept queries that include numeric criteria, parameters, or arguments, including query attributes represented by numeric values, which may be in different units or scales, and attributes represented by numeric values that can vary by time.