Abstract: A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables where the cost functions have a relationship with the variables and receiving a landmark indicating a point that an agent is to visit while moving, a cost being associated with ignoring the landmark. The method includes generating a first message for the cost functions for the corresponding variable based upon the relationship and a second message for each of the variables for the corresponding cost function based upon the relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes repeating steps (c), (d), and (e) until a consensus is formed between the first and second messages until the optimization solution is determined based upon the consensus.

Abstract: A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables in which each of the cost functions has a predetermined relationship with select ones of the variables. The variables comprise a sub-solution of a spline indicative of a curved path along an estimated trajectory. The method includes generating a first message for each of the cost functions for each corresponding variable based upon the relationship and a second message for each of the variables for each corresponding cost function based upon the relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes forming a consensus between the first and second messages until the optimization solution is determined.

Abstract: A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables where the cost functions have a relationship with the variables and receiving a landmark indicating a point that an agent is to visit while moving, a cost being associated with ignoring the landmark. The method includes generating a first message for the cost functions for the corresponding variable based upon the relationship and a second message for each of the variables for the corresponding cost function based upon the relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes repeating steps (c), (d), and (e) until a consensus is formed between the first and second messages until the optimization solution is determined based upon the consensus.

Abstract: A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables in which each of the cost functions has a predetermined relationship with select ones of the variables. The method includes generating a first message for each of the cost functions for each corresponding variable based upon the respective predetermined relationship and a second message for each of the variables for each corresponding cost function based upon the respective predetermined relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes repeating steps (b), (c), and (d) until a consensus is formed between the first and second messages until the optimization solution is determined based upon the consensus.

Abstract: A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables in which each of the cost functions has a predetermined relationship with select ones of the variables. The variables comprise a sub-solution of a spline indicative of a curved path along an estimated trajectory. The method includes generating a first message for each of the cost functions for each corresponding variable based upon the relationship and a second message for each of the variables for each corresponding cost function based upon the relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes forming a consensus between the first and second messages until the optimization solution is determined.

Abstract: A method and device determines an optimization solution for an optimization problem. The method includes receiving the optimization problem having cost functions and variables in which each of the cost functions has a predetermined relationship with select ones of the variables. The method includes generating a first message for each of the cost functions for each corresponding variable based upon the respective predetermined relationship and a second message for each of the variables for each corresponding cost function based upon the respective predetermined relationship. The method includes generating a disagreement variable for each corresponding pair of variables and cost functions measuring a disagreement value between the first and second beliefs. The method includes repeating steps (b), (c), and (d) until a consensus is formed between the first and second messages until the optimization solution is determined based upon the consensus.