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CmaOptimizer {
signature_prefix = DATE_TIME
# use previous result
# init_file = data/CMJ/ResultStandingHigh_CMJ_Jump.par 
SimulationObjective {
# max_duration = 10
# Model used in simulation
OpenSimModel {
model_file = data/CMJ/Human0916_CMJ.osim
}
# Composite measure for straight pose jumping
CompositeMeasure {
dual_sided = 1
minimize = 1 # Minimize this measure
# MimicMeasure for Jump
MimicMeasure {
file = data/CMJ/inverse_dynamics.sto
#
include_states = *.
}
# Penalize high effort
EffortMeasure {
measure_type = TotalForce
}
}
}
}

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CompositeMeasure {
	MimicMeasure {
		name = Mimic
		weight = 100
		file = ...
		include_states = "*" # select the states you want to mimic
		threshold = 0.01
		average_error_limit = 0.01
	}
	
	# cost-of-transport
	EffortMeasure {
		name = Effort
		weight = 0.1
		measure_type = Wang2012
	}
}

Code: Select all

CmaOptimizer {
	signature_prefix = DATE_TIME
	# use previous result
	# init_file = data/CMJ/ResultStandingHigh_CMJ_Jump.par 
	
	SimulationObjective {
		
		# Model used in simulation
		OpenSimModel {
			model_file = data/CMJ/Human0916_CMJ.osim
		}
		
		# Composite measure for mimic and cost of transport
		CompositeMeasure {
			MimicMeasure {
				name = Mimic
				weight = 100
				file = subject01_walk1_RRA_Actuation_force
				include_states = "*" # select the states you want to mimic
				threshold = 0.01
				average_error_limit = 0.01
			}
	
			# cost-of-transport
			EffortMeasure {
				name = Effort
				weight = 0.1
				measure_type = Wang2012
			}
		}
	}
	
}

Code: Select all

CmaOptimizer {
	signature_prefix = DATE_TIME
	# use previous result
	# init_file = data/CMJ/ResultStandingHigh_CMJ_Jump.par 
	
	SimulationObjective {
		
		# Model used in simulation
		OpenSimModel {
			model_file = data/CMJ/Human0916_CMJ.osim
		}
		
		# Controller based on lua script
		ScriptController {
			script_file = "data/CMJ/ScriptController_CMJ_Jump.lua"
		}
		
		# Composite measure for mimic and cost of transport
		CompositeMeasure {
			# mimic the .sto file
			MimicMeasure {
				name = Mimic
				start_time = 3
				stop_time = 5
				weight = 100
				file = data/CMJ/xxx_DropJump1_RRA_Kinematics_q.sto
				include_states = "*" # select the states you want to mimic
				threshold = 0.01
				average_error_limit = 0.01
			}
			
			# cost-of-transport
			EffortMeasure {
				name = Effort
				weight = 0.1
				measure_type = Wang2012
			}
		}
		
	}
	
}

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-- SCONE script for a simple feed-forward controller.
-- See Tutorial 6a - Script - High Jump

function init( model, par )
	-- keep a list of offsets and slopes to compute the excitation
	offset = {}
	slope = {}

	-- keep a list of all actuators
	actuators = {}

	-- iterate over all actuators in the model
	for i = 1, model:actuator_count() do
		-- store the actuator in the list
		actuators[ i ] = model:actuator( i )

		-- create parameters for both slope and offset
		local name = actuators[ i ]:name()
		offset[ i ] = par:create_from_mean_std( name .. "-offset", 0.3, 0.1, 0, 1 )
		slope[ i ] = par:create_from_mean_std( name .. "-slope", 0, 1, -10, 10 )
	end
end

function update( model )
	-- get the current simulation time
	local t = model:time()

	-- iterate over all actuators
	for i = 1, #actuators do
		local excitation = offset[ i ] + t * slope[ i ]
		actuators[ i ]:add_input( excitation )
	end
end

Code: Select all

CmaOptimizer {
	signature_prefix = DATE_TIME
	# use previous result
	init_file = data/CMJ/ResultStandingHigh_CMJ_Jump.par 
	
	SimulationObjective {
		max_duration = 5 #from 2
		
		# Model used in simulation
		OpenSimModel {
			model_file = data/CMJ/Human0916_CMJ.osim
		}
		
		# Controller for the Model
		FeedForwardController {
			symmetric = 0
			
			# Function for feed-forward pattern
			PieceWiseConstant {
				control_points = 2 # from 2
				control_point_y = 0.3~0.01<0,1> # Initial y value of control points
				control_point_dt = 0.2~0.01<0.001,1> # Initial delta time between control points
			}
		}
		
		# Composite measure for mimic and cost of transport
		CompositeMeasure {
			# mimic the .sto file
			MimicMeasure {
				name = Mimic
				start_time = 2
				stop_time = 5
				weight = 100
				file = data/CMJ/Pirovano2392_DropJump1_RRA_Kinematics_q.sto
				include_states = "*" # select the states you want to mimic
				threshold = 0.01
				average_error_limit = 0.01
			}
			
			# cost-of-transport
			EffortMeasure {
				name = Effort
				weight = 0.1
				measure_type = Wang2012
			}
		}
		
	}
	
}